Date: (Mon) Apr 20, 2015

Introduction:

Data: Source: Training: https://courses.edx.org/c4x/MITx/15.071x_2/asset/ClaimsData.csv.zip
New:
Time period:

Synopsis:

Based on analysis utilizing <> techniques, :

[](.png)

Potential next steps include:

  • Probability handling for multinomials vs. desired binomial outcome
  • ROCR currently supports only evaluation of binary classification tasks (version 1.0.7)
  • extensions toward multiclass classification are scheduled for the next release

  • Skip trControl.method=“cv” for dummy classifier ?
  • Add custom model to caret for a dummy (baseline) classifier (binomial & multinomial) that generates proba/outcomes which mimics the freq distribution of glb_rsp_var values; Right now glb_dmy_glm_mdl always generates most frequent outcome in training data
  • glm_dmy_mdl should use the same method as glm_sel_mdl until custom dummy classifer is implemented

  • Compare glb_sel_mdl vs. glb_fin_mdl:
    • varImp
    • Prediction differences (shd be minimal ?)
  • Prediction accuracy scatter graph:
  • Add tiles (raw vs. PCA)
  • Use shiny for drop-down of “important” features
  • Use plot.ly for interactive plots ?

  • Move glb_analytics_diag_plots to mydsutils.R: (+) Easier to debug (-) Too many glb vars used
  • Add print(ggplot.petrinet(glb_analytics_pn) + coord_flip()) at the end of every major chunk
  • Parameterize glb_analytics_pn
  • Move glb_impute_missing_data to mydsutils.R: (-) Too many glb vars used; glb_<>_df reassigned
  • Replicate myfit_mdl_classification features in myfit_mdl_regression
  • Do non-glm methods handle interaction terms ?
  • f-score computation for classifiers should be summation across outcomes (not just the desired one ?)
  • Add accuracy computation to glb_dmy_mdl in predict.data.new chunk
  • Why does splitting fit.data.training.all chunk into separate chunks add an overhead of ~30 secs ? It’s not rbind b/c other chunks have lower elapsed time. Is it the number of plots ?
  • Incorporate code chunks in print_sessionInfo
  • Test against
    • projects in github.com/bdanalytics
    • lectures in jhu-datascience track

Analysis:

rm(list=ls())
set.seed(12345)
options(stringsAsFactors=FALSE)
source("~/Dropbox/datascience/R/mydsutils.R")
source("~/Dropbox/datascience/R/myplot.R")
source("~/Dropbox/datascience/R/mypetrinet.R")
# Gather all package requirements here
#suppressPackageStartupMessages(require())
#packageVersion("caret")

#require(sos); findFn("pinv", maxPages=2, sortby="MaxScore")

# Analysis control global variables
glb_trnng_url <- "https://courses.edx.org/c4x/MITx/15.071x_2/asset/ClaimsData.csv.zip"
glb_newdt_url <- "<newdt_url>"
glb_is_separate_newent_dataset <- FALSE    # or TRUE
glb_split_entity_newent_datasets <- TRUE   # or FALSE
glb_split_newdata_method <- "sample"          # "condition" or "sample"
glb_split_newdata_condition <- "<col_name> <condition_operator> <value>"    # or NULL
glb_split_newdata_size_ratio <- 0.4               # > 0 & < 1
glb_split_sample.seed <- 88               # or any integer
glb_max_obs <- 20000 # or NULL

glb_is_regression <- FALSE; glb_is_classification <- TRUE

glb_rsp_var_raw <- "bucket2009"

# for classification, the response variable has to be a factor
#   especially for random forests (method="rf")
glb_rsp_var <- "bucket2009.fctr"    # or glb_rsp_var_raw

# if the response factor is based on numbers e.g (0/1 vs. "A"/"B"), 
#   caret predict(..., type="prob") crashes
glb_map_rsp_raw_to_var <- function(raw) {
    as.factor(paste0("B", raw))
} # or NULL
#glb_map_rsp_raw_to_var(c(1, 2, 3, 4, 5))

glb_map_rsp_var_to_raw <- function(var) {
    as.numeric(var)
} # or NULL
#glb_map_rsp_var_to_raw(glb_map_rsp_raw_to_var(c(1, 2, 3, 4, 5)))

if ((glb_rsp_var != glb_rsp_var_raw) & is.null(glb_map_rsp_raw_to_var))
    stop("glb_map_rsp_raw_to_var function expected")

glb_rsp_var_out <- paste0(glb_rsp_var, ".predict.") # model_id is appended later
glb_id_vars <- NULL # or c("<id_var>")

# List transformed vars  
glb_exclude_vars_as_features <- c("bucket2008.fctr")     # or c(NULL)
# List feats that shd be excluded due to known causation by prediction variable
if (glb_rsp_var_raw != glb_rsp_var)
    glb_exclude_vars_as_features <- union(glb_exclude_vars_as_features, 
                                            glb_rsp_var_raw)
glb_exclude_vars_as_features <- union(glb_exclude_vars_as_features, 
                                      c("reimbursement2009")) # or NULL
# List output vars (useful during testing in console)          
# glb_exclude_vars_as_features <- union(glb_exclude_vars_as_features, 
#                         grep(glb_rsp_var_out, names(glb_entity_df), value=TRUE)) 

glb_impute_na_data <- FALSE            # or TRUE
glb_mice_complete.seed <- 144               # or any integer

# Classification
#   rpart:  .rnorm messes with the models badly
#           caret creates dummy vars for factor feats which messes up the tuning
#               - better to feed as.numeric(<feat>.fctr) to caret 

#glb_models_method_vctr <- c("glm", "rpart", "rf")   # Binomials
#glb_models_method_vctr <- c("rpart", "rf")          # Multinomials
glb_models_method_vctr <- c("rpart")          # Multinomials - this exercise

glb_models_lst <- list(); glb_models_df <- data.frame()
# Baseline prediction model feature(s)
glb_Baseline_mdl_var <- c("bucket2008.fctr") # or NULL

glb_model_metric_terms <- matrix(c(
                              0,1,2,3,4,
                              2,0,1,2,3,
                              4,2,0,1,2,
                              6,4,2,0,1,
                              8,6,4,2,0
                          ), byrow=TRUE, nrow=5)    # or NULL
glb_model_metric <- "loss.error" # or NULL
glb_model_metric_maximize <- FALSE # or NULL (TRUE is not the default for both classification & regression) 
glb_model_metric_smmry <- function(data, lev=NULL, model=NULL) {
    confusion_mtrx <- t(as.matrix(confusionMatrix(data$pred, data$obs)))
    #print(confusion_mtrx)
    #print(confusion_mtrx * glb_model_metric_terms)
    metric <- sum(confusion_mtrx * glb_model_metric_terms) / nrow(data)
    names(metric) <- glb_model_metric
    return(metric)
}

glb_tune_models_df <- 
   rbind(
    data.frame(parameter="cp", min=0.00005, max=0.00005, by=0.000005),
                              #min=0.00004; max=0.00006; by=0.000005
    #data.frame(parameter="mtry", min=2, max=4, by=1),
    data.frame(parameter="dummy", min=2, max=4, by=1)
        ) 
# or NULL
glb_n_cv_folds <- 5 # or NULL

glb_clf_proba_threshold <- NULL # 0.5

# Model selection criteria
# For binomial classification add AIC
glb_model_sel_frmla <- formula(paste0("~ ", 
    ifelse(!is.null(glb_model_metric), 
        paste0(ifelse(!glb_model_metric_maximize, "+min.", "-max."), 
               paste0(glb_model_metric, ".OOB")), 
           ""), " -max.Accuracy.OOB -max.Kappa.OOB"))

glb_sel_mdl_id <- "All.X.lser.ys.cp.4015.rpart" # or NULL
glb_fin_mdl_id <- glb_sel_mdl_id # or "Final"

# Depict process
glb_analytics_pn <- petrinet(name="glb_analytics_pn",
                        trans_df=data.frame(id=1:6,
    name=c("data.training.all","data.new",
           "model.selected","model.final",
           "data.training.all.prediction","data.new.prediction"),
    x=c(   -5,-5,-15,-25,-25,-35),
    y=c(   -5, 5,  0,  0, -5,  5)
                        ),
                        places_df=data.frame(id=1:4,
    name=c("bgn","fit.data.training.all","predict.data.new","end"),
    x=c(   -0,   -20,                    -30,               -40),
    y=c(    0,     0,                      0,                 0),
    M0=c(   3,     0,                      0,                 0)
                        ),
                        arcs_df=data.frame(
    begin=c("bgn","bgn","bgn",        
            "data.training.all","model.selected","fit.data.training.all",
            "fit.data.training.all","model.final",    
            "data.new","predict.data.new",
            "data.training.all.prediction","data.new.prediction"),
    end  =c("data.training.all","data.new","model.selected",
            "fit.data.training.all","fit.data.training.all","model.final",
            "data.training.all.prediction","predict.data.new",
            "predict.data.new","data.new.prediction",
            "end","end")
                        ))
#print(ggplot.petrinet(glb_analytics_pn))
print(ggplot.petrinet(glb_analytics_pn) + coord_flip())
## Loading required package: grid

glb_analytics_avl_objs <- NULL

glb_script_tm <- proc.time()
glb_script_df <- data.frame(chunk_label="import_data", 
                            chunk_step_major=1, chunk_step_minor=0,
                            elapsed=(proc.time() - glb_script_tm)["elapsed"])
print(tail(glb_script_df, 2))
##         chunk_label chunk_step_major chunk_step_minor elapsed
## elapsed import_data                1                0   0.003

Step 1: import data

glb_entity_df <- myimport_data(
    url=glb_trnng_url, 
    comment="glb_entity_df", force_header=TRUE,
    print_diagn=(glb_is_separate_newent_dataset | 
                !glb_split_entity_newent_datasets))
## [1] "Reading file ./data/ClaimsData.csv..."
## [1] "dimensions of data in ./data/ClaimsData.csv: 458,005 rows x 16 cols"
if (glb_is_separate_newent_dataset) {
    glb_newent_df <- myimport_data(
        url=glb_newdt_url, 
        comment="glb_newent_df", force_header=TRUE, print_diagn=TRUE)
} else {
    if (!glb_split_entity_newent_datasets) {
        stop("Not implemented yet") 
        glb_newent_df <- glb_entity_df[sample(1:nrow(glb_entity_df),
                                          max(2, nrow(glb_entity_df) / 1000)),]                    
    } else      if (glb_split_newdata_method == "condition") {
            glb_newent_df <- do.call("subset", 
                list(glb_entity_df, parse(text=glb_split_newdata_condition)))
            glb_entity_df <- do.call("subset", 
                list(glb_entity_df, parse(text=paste0("!(", 
                                                      glb_split_newdata_condition,
                                                      ")"))))
        } else if (glb_split_newdata_method == "sample") {
                require(caTools)
                
                set.seed(glb_split_sample.seed)
                split <- sample.split(glb_entity_df[, glb_rsp_var_raw], 
                                      SplitRatio=(1-glb_split_newdata_size_ratio))
                glb_newent_df <- glb_entity_df[!split, ] 
                glb_entity_df <- glb_entity_df[split ,]
        } else stop("glb_split_newdata_method should be %in% c('condition', 'sample')")   

    comment(glb_newent_df) <- "glb_newent_df"
    myprint_df(glb_newent_df)
    str(glb_newent_df)

    if (glb_split_entity_newent_datasets) {
        myprint_df(glb_entity_df)
        str(glb_entity_df)        
    }
}         
## Loading required package: caTools
##    age alzheimers arthritis cancer copd depression diabetes heart.failure
## 3   67          0         0      0    0          0        0             0
## 5   67          0         0      0    0          0        0             0
## 6   68          0         0      0    0          0        0             0
## 8   70          0         0      0    0          0        0             0
## 9   67          0         0      0    0          0        0             0
## 10  67          0         0      0    0          0        0             0
##    ihd kidney osteoporosis stroke reimbursement2008 bucket2008
## 3    0      0            0      0                 0          1
## 5    0      0            0      0                 0          1
## 6    0      0            0      0                 0          1
## 8    0      0            0      0                 0          1
## 9    0      0            0      0                 0          1
## 10   0      0            0      0                 0          1
##    reimbursement2009 bucket2009
## 3                  0          1
## 5                  0          1
## 6                  0          1
## 8                  0          1
## 9                  0          1
## 10                 0          1
##        age alzheimers arthritis cancer copd depression diabetes
## 43967   57          0         0      0    0          0        0
## 70246   70          0         0      0    0          0        0
## 165755  78          0         0      0    0          0        0
## 208131  73          0         1      1    0          0        0
## 319113  87          0         0      0    0          1        1
## 446073  72          1         0      1    0          1        1
##        heart.failure ihd kidney osteoporosis stroke reimbursement2008
## 43967              0   0      0            0      0                 0
## 70246              0   0      0            0      0                 0
## 165755             0   0      0            0      0               140
## 208131             0   0      0            1      0              5680
## 319113             0   1      0            0      0              2800
## 446073             1   1      0            1      1             16030
##        bucket2008 reimbursement2009 bucket2009
## 43967           1                 0          1
## 70246           1                 0          1
## 165755          1               720          1
## 208131          2              1250          1
## 319113          1              3330          2
## 446073          3             28000          4
##        age alzheimers arthritis cancer copd depression diabetes
## 457996  60          0         1      0    1          1        1
## 457998  87          0         0      0    1          1        1
## 458001  61          1         0      0    1          1        1
## 458002  90          1         0      0    1          1        1
## 458003  76          0         1      0    1          1        1
## 458005  80          1         0      0    1          1        1
##        heart.failure ihd kidney osteoporosis stroke reimbursement2008
## 457996             1   1      0            1      1             11720
## 457998             1   1      1            0      0             27750
## 458001             1   1      1            1      1             15960
## 458002             1   1      1            0      0             26870
## 458003             1   1      1            1      1             89140
## 458005             1   1      1            0      1             38320
##        bucket2008 reimbursement2009 bucket2009
## 457996          3            142960          5
## 457998          4            148600          5
## 458001          3            154000          5
## 458002          4            155010          5
## 458003          5            155810          5
## 458005          4            189930          5
## 'data.frame':    183202 obs. of  16 variables:
##  $ age              : int  67 67 68 70 67 67 56 48 99 68 ...
##  $ alzheimers       : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ arthritis        : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ cancer           : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ copd             : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ depression       : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ diabetes         : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ heart.failure    : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ ihd              : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ kidney           : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ osteoporosis     : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ stroke           : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ reimbursement2008: int  0 0 0 0 0 0 0 0 0 0 ...
##  $ bucket2008       : int  1 1 1 1 1 1 1 1 1 1 ...
##  $ reimbursement2009: int  0 0 0 0 0 0 0 0 0 0 ...
##  $ bucket2009       : int  1 1 1 1 1 1 1 1 1 1 ...
##  - attr(*, "comment")= chr "glb_newent_df"
##    age alzheimers arthritis cancer copd depression diabetes heart.failure
## 1   85          0         0      0    0          0        0             0
## 2   59          0         0      0    0          0        0             0
## 4   52          0         0      0    0          0        0             0
## 7   75          0         0      0    0          0        0             0
## 11  89          0         0      0    0          0        0             0
## 13  74          0         0      0    0          0        0             0
##    ihd kidney osteoporosis stroke reimbursement2008 bucket2008
## 1    0      0            0      0                 0          1
## 2    0      0            0      0                 0          1
## 4    0      0            0      0                 0          1
## 7    0      0            0      0                 0          1
## 11   0      0            0      0                 0          1
## 13   0      0            0      0                 0          1
##    reimbursement2009 bucket2009
## 1                  0          1
## 2                  0          1
## 4                  0          1
## 7                  0          1
## 11                 0          1
## 13                 0          1
##        age alzheimers arthritis cancer copd depression diabetes
## 138659  69          0         0      0    0          0        0
## 168428  74          1         0      0    0          0        1
## 189703  81          0         0      0    0          0        1
## 225640  78          1         0      0    0          1        0
## 382169  77          1         0      0    1          1        1
## 397881  46          1         0      0    0          0        0
##        heart.failure ihd kidney osteoporosis stroke reimbursement2008
## 138659             0   0      0            0      0                 0
## 168428             0   0      0            1      0               720
## 189703             0   1      0            0      0               690
## 225640             0   0      0            1      0              1540
## 382169             1   1      1            1      1             16400
## 397881             1   1      1            0      0              3700
##        bucket2008 reimbursement2009 bucket2009
## 138659          1               380          1
## 168428          1               750          1
## 189703          1              1020          1
## 225640          1              1490          1
## 382169          3              6620          2
## 397881          2              8470          3
##        age alzheimers arthritis cancer copd depression diabetes
## 457991  76          0         0      0    1          1        1
## 457992  84          0         0      0    1          0        1
## 457997  73          0         0      0    1          1        1
## 457999  83          1         1      0    1          0        1
## 458000  56          0         1      0    1          1        1
## 458004  82          1         0      0    1          0        1
##        heart.failure ihd kidney osteoporosis stroke reimbursement2008
## 457991             1   1      1            1      0             53550
## 457992             1   1      1            0      0              8620
## 457997             1   1      1            1      0             53230
## 457999             1   1      1            1      1             62620
## 458000             1   1      1            1      0             62980
## 458004             1   1      1            1      1             20660
##        bucket2008 reimbursement2009 bucket2009
## 457991          4            131960          5
## 457992          3            133500          5
## 457997          4            147760          5
## 457999          5            148860          5
## 458000          5            151880          5
## 458004          4            158800          5
## 'data.frame':    274803 obs. of  16 variables:
##  $ age              : int  85 59 52 75 89 74 81 86 78 67 ...
##  $ alzheimers       : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ arthritis        : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ cancer           : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ copd             : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ depression       : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ diabetes         : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ heart.failure    : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ ihd              : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ kidney           : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ osteoporosis     : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ stroke           : int  0 0 0 0 0 0 0 0 0 0 ...
##  $ reimbursement2008: int  0 0 0 0 0 0 0 0 0 0 ...
##  $ bucket2008       : int  1 1 1 1 1 1 1 1 1 1 ...
##  $ reimbursement2009: int  0 0 0 0 0 0 0 0 0 0 ...
##  $ bucket2009       : int  1 1 1 1 1 1 1 1 1 1 ...
##  - attr(*, "comment")= chr "glb_entity_df"
if (!is.null(glb_max_obs)) {
    if (nrow(glb_entity_df) > glb_max_obs) {
        warning("glb_entity_df restricted to glb_max_obs: ", format(glb_max_obs, big.mark=","))
        org_entity_df <- glb_entity_df
        glb_entity_df <- org_entity_df[split <- 
            sample.split(org_entity_df[, glb_rsp_var_raw], SplitRatio=glb_max_obs), ]
        org_entity_df <- NULL
    }
    if (nrow(glb_newent_df) > glb_max_obs) {
        warning("glb_newent_df restricted to glb_max_obs: ", format(glb_max_obs, big.mark=","))        
        org_newent_df <- glb_newent_df
        glb_newent_df <- org_newent_df[split <- 
            sample.split(org_newent_df[, glb_rsp_var_raw], SplitRatio=glb_max_obs), ]
        org_newent_df <- NULL
    }    
}
## Warning: glb_entity_df restricted to glb_max_obs: 20,000
## Warning: glb_newent_df restricted to glb_max_obs: 20,000
glb_script_df <- rbind(glb_script_df,
                   data.frame(chunk_label="cleanse_data", 
                              chunk_step_major=max(glb_script_df$chunk_step_major)+1, 
                              chunk_step_minor=0,
                              elapsed=(proc.time() - glb_script_tm)["elapsed"]))
print(tail(glb_script_df, 2))
##           chunk_label chunk_step_major chunk_step_minor elapsed
## elapsed   import_data                1                0   0.003
## elapsed1 cleanse_data                2                0   6.674

Step 2: cleanse data

glb_script_df <- rbind(glb_script_df, 
                   data.frame(chunk_label="inspectORexplore.data", 
                              chunk_step_major=max(glb_script_df$chunk_step_major), 
                              chunk_step_minor=1,
                              elapsed=(proc.time() - glb_script_tm)["elapsed"]))
print(tail(glb_script_df, 2))
##                    chunk_label chunk_step_major chunk_step_minor elapsed
## elapsed1          cleanse_data                2                0   6.674
## elapsed2 inspectORexplore.data                2                1   6.707

Step 2.1: inspect/explore data

#print(str(glb_entity_df))
#View(glb_entity_df)

# List info gathered for various columns
# <col_name>:   <description>; <notes>

# Create new features that help diagnostics
#   Create factors of string variables
str_vars <- sapply(1:length(names(glb_entity_df)), 
    function(col) ifelse(class(glb_entity_df[, names(glb_entity_df)[col]]) == "character",
                         names(glb_entity_df)[col], ""))
if (length(str_vars <- setdiff(str_vars[str_vars != ""], 
                               glb_exclude_vars_as_features)) > 0) {
    warning("Creating factors of string variables:", paste0(str_vars, collapse=", "))
    glb_exclude_vars_as_features <- union(glb_exclude_vars_as_features, str_vars)
    for (var in str_vars) {
        glb_entity_df[, paste0(var, ".fctr")] <- factor(glb_entity_df[, var], 
                        as.factor(union(glb_entity_df[, var], glb_newent_df[, var])))
        glb_newent_df[, paste0(var, ".fctr")] <- factor(glb_newent_df[, var], 
                        as.factor(union(glb_entity_df[, var], glb_newent_df[, var])))
    }
}

#   Convert factors to dummy variables
#   Build splines   require(splines); bsBasis <- bs(training$age, df=3)

add_new_diag_feats <- function(obs_df, obs_twin_df) {
    require(plyr)
    
    obs_df <- mutate(obs_df,
#         <col_name>.NA=is.na(<col_name>),

#         <col_name>.fctr=factor(<col_name>, 
#                     as.factor(union(obs_df$<col_name>, obs_twin_df$<col_name>))), 
#         <col_name>.fctr=relevel(factor(<col_name>, 
#                     as.factor(union(obs_df$<col_name>, obs_twin_df$<col_name>))),
#                                   "<ref_val>"), 
#         <col2_name>.fctr=relevel(factor(ifelse(<col1_name> == <val>, "<oth_val>", "<ref_val>")), 
#                               as.factor(c("R", "<ref_val>")),
#                               ref="<ref_val>"),

          # This doesn't work - use sapply instead
#         <col_name>.fctr_num=grep(<col_name>, levels(<col_name>.fctr)), 
#         
#         Date.my=as.Date(strptime(Date, "%m/%d/%y %H:%M")),
#         Year=year(Date.my),
#         Month=months(Date.my),
#         Weekday=weekdays(Date.my)

#         <col_name>.log=log(<col.name>),        
#         <col_name>=<table>[as.character(<col2_name>)],
#         <col_name>=as.numeric(<col2_name>),

        .rnorm=rnorm(n=nrow(obs_df))
                        )

    # If levels of a factor are different across obs_df & glb_newent_df; predict.glm fails  
    # Transformations not handled by mutate
#     obs_df$<col_name>.fctr.num <- sapply(1:nrow(obs_df), 
#         function(row_ix) grep(obs_df[row_ix, "<col_name>"],
#                               levels(obs_df[row_ix, "<col_name>.fctr"])))
    
    print(summary(obs_df))
    print(sapply(names(obs_df), function(col) sum(is.na(obs_df[, col]))))
    return(obs_df)
}

glb_entity_df <- add_new_diag_feats(glb_entity_df, glb_newent_df)
## Loading required package: plyr
##       age           alzheimers       arthritis          cancer       
##  Min.   : 26.00   Min.   :0.0000   Min.   :0.0000   Min.   :0.00000  
##  1st Qu.: 67.00   1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.00000  
##  Median : 73.00   Median :0.0000   Median :0.0000   Median :0.00000  
##  Mean   : 72.55   Mean   :0.1917   Mean   :0.1542   Mean   :0.06325  
##  3rd Qu.: 81.00   3rd Qu.:0.0000   3rd Qu.:0.0000   3rd Qu.:0.00000  
##  Max.   :100.00   Max.   :1.0000   Max.   :1.0000   Max.   :1.00000  
##       copd          depression        diabetes      heart.failure   
##  Min.   :0.0000   Min.   :0.0000   Min.   :0.0000   Min.   :0.0000  
##  1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.0000  
##  Median :0.0000   Median :0.0000   Median :0.0000   Median :0.0000  
##  Mean   :0.1361   Mean   :0.2118   Mean   :0.3788   Mean   :0.2854  
##  3rd Qu.:0.0000   3rd Qu.:0.0000   3rd Qu.:1.0000   3rd Qu.:1.0000  
##  Max.   :1.0000   Max.   :1.0000   Max.   :1.0000   Max.   :1.0000  
##       ihd             kidney        osteoporosis        stroke       
##  Min.   :0.0000   Min.   :0.0000   Min.   :0.0000   Min.   :0.00000  
##  1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.00000  
##  Median :0.0000   Median :0.0000   Median :0.0000   Median :0.00000  
##  Mean   :0.4214   Mean   :0.1656   Mean   :0.1758   Mean   :0.04225  
##  3rd Qu.:1.0000   3rd Qu.:0.0000   3rd Qu.:0.0000   3rd Qu.:0.00000  
##  Max.   :1.0000   Max.   :1.0000   Max.   :1.0000   Max.   :1.00000  
##  reimbursement2008   bucket2008    reimbursement2009   bucket2009   
##  Min.   :     0    Min.   :1.000   Min.   :     0    Min.   :1.000  
##  1st Qu.:     0    1st Qu.:1.000   1st Qu.:   140    1st Qu.:1.000  
##  Median :   950    Median :1.000   Median :  1510    Median :1.000  
##  Mean   :  4027    Mean   :1.435   Mean   :  4263    Mean   :1.522  
##  3rd Qu.:  3080    3rd Qu.:2.000   3rd Qu.:  4242    3rd Qu.:2.000  
##  Max.   :193590    Max.   :5.000   Max.   :148860    Max.   :5.000  
##      .rnorm         
##  Min.   :-3.817081  
##  1st Qu.:-0.687574  
##  Median : 0.006919  
##  Mean   :-0.000529  
##  3rd Qu.: 0.688151  
##  Max.   : 3.616434  
##               age        alzheimers         arthritis            cancer 
##                 0                 0                 0                 0 
##              copd        depression          diabetes     heart.failure 
##                 0                 0                 0                 0 
##               ihd            kidney      osteoporosis            stroke 
##                 0                 0                 0                 0 
## reimbursement2008        bucket2008 reimbursement2009        bucket2009 
##                 0                 0                 0                 0 
##            .rnorm 
##                 0
glb_newent_df <- add_new_diag_feats(glb_newent_df, glb_entity_df)
##       age           alzheimers       arthritis          cancer       
##  Min.   : 26.00   Min.   :0.0000   Min.   :0.0000   Min.   :0.00000  
##  1st Qu.: 67.00   1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.00000  
##  Median : 73.00   Median :0.0000   Median :0.0000   Median :0.00000  
##  Mean   : 72.56   Mean   :0.1898   Mean   :0.1507   Mean   :0.06255  
##  3rd Qu.: 81.00   3rd Qu.:0.0000   3rd Qu.:0.0000   3rd Qu.:0.00000  
##  Max.   :100.00   Max.   :1.0000   Max.   :1.0000   Max.   :1.00000  
##       copd          depression        diabetes      heart.failure   
##  Min.   :0.0000   Min.   :0.0000   Min.   :0.0000   Min.   :0.0000  
##  1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.0000  
##  Median :0.0000   Median :0.0000   Median :0.0000   Median :0.0000  
##  Mean   :0.1313   Mean   :0.2136   Mean   :0.3755   Mean   :0.2772  
##  3rd Qu.:0.0000   3rd Qu.:0.0000   3rd Qu.:1.0000   3rd Qu.:1.0000  
##  Max.   :1.0000   Max.   :1.0000   Max.   :1.0000   Max.   :1.0000  
##       ihd             kidney       osteoporosis        stroke      
##  Min.   :0.0000   Min.   :0.000   Min.   :0.0000   Min.   :0.0000  
##  1st Qu.:0.0000   1st Qu.:0.000   1st Qu.:0.0000   1st Qu.:0.0000  
##  Median :0.0000   Median :0.000   Median :0.0000   Median :0.0000  
##  Mean   :0.4176   Mean   :0.161   Mean   :0.1696   Mean   :0.0439  
##  3rd Qu.:1.0000   3rd Qu.:0.000   3rd Qu.:0.0000   3rd Qu.:0.0000  
##  Max.   :1.0000   Max.   :1.000   Max.   :1.0000   Max.   :1.0000  
##  reimbursement2008   bucket2008    reimbursement2009   bucket2009   
##  Min.   :     0    Min.   :1.000   Min.   :     0    Min.   :1.000  
##  1st Qu.:     0    1st Qu.:1.000   1st Qu.:   110    1st Qu.:1.000  
##  Median :   930    Median :1.000   Median :  1510    Median :1.000  
##  Mean   :  3980    Mean   :1.432   Mean   :  4279    Mean   :1.522  
##  3rd Qu.:  3050    3rd Qu.:2.000   3rd Qu.:  4170    3rd Qu.:2.000  
##  Max.   :141660    Max.   :5.000   Max.   :155810    Max.   :5.000  
##      .rnorm         
##  Min.   :-4.252950  
##  1st Qu.:-0.666528  
##  Median : 0.004632  
##  Mean   :-0.001022  
##  3rd Qu.: 0.680051  
##  Max.   : 3.818579  
##               age        alzheimers         arthritis            cancer 
##                 0                 0                 0                 0 
##              copd        depression          diabetes     heart.failure 
##                 0                 0                 0                 0 
##               ihd            kidney      osteoporosis            stroke 
##                 0                 0                 0                 0 
## reimbursement2008        bucket2008 reimbursement2009        bucket2009 
##                 0                 0                 0                 0 
##            .rnorm 
##                 0
# Histogram of predictor in glb_entity_df & glb_newent_df
print(myplot_histogram(glb_entity_df, glb_rsp_var_raw))
## stat_bin: binwidth defaulted to range/30. Use 'binwidth = x' to adjust this.

if (glb_is_classification)
    print(table(glb_entity_df[, glb_rsp_var_raw]) / nrow(glb_entity_df))
## 
##       1       2       3       4       5 
## 0.67130 0.19015 0.08945 0.04335 0.00575
print(myplot_histogram(glb_newent_df, glb_rsp_var_raw))
## stat_bin: binwidth defaulted to range/30. Use 'binwidth = x' to adjust this.

# Check for duplicates in glb_id_vars
if (length(glb_id_vars) > 0) {
    id_vars_dups_df <- subset(id_vars_df <- mycreate_tbl_df(
        rbind(glb_entity_df[, glb_id_vars, FALSE], glb_newent_df[, glb_id_vars, FALSE]),
            glb_id_vars), .freq > 1)
    if (nrow(id_vars_dups_df) > 0) {
        warning("Duplicates found in glb_id_vars data:", nrow(id_vars_dups_df))
        myprint_df(id_vars_dups_df)
    } else {
        # glb_id_vars are unique across obs in both glb_<>_df
        glb_exclude_vars_as_features <- union(glb_exclude_vars_as_features, glb_id_vars)
    }
}

#pairs(subset(glb_entity_df, select=-c(col_symbol)))
# Check for glb_newent_df & glb_entity_df features range mismatches

# Other diagnostics:
# print(subset(glb_entity_df, <col1_name> == max(glb_entity_df$<col1_name>, na.rm=TRUE) & 
#                         <col2_name> <= mean(glb_entity_df$<col1_name>, na.rm=TRUE)))

# print(glb_entity_df[which.max(glb_entity_df$<col_name>),])

# print(<col_name>_freq_glb_entity_df <- mycreate_tbl_df(glb_entity_df, "<col_name>"))
# print(which.min(table(glb_entity_df$<col_name>)))
# print(which.max(table(glb_entity_df$<col_name>)))
# print(which.max(table(glb_entity_df$<col1_name>, glb_entity_df$<col2_name>)[, 2]))
# print(table(glb_entity_df$<col1_name>, glb_entity_df$<col2_name>))
# print(table(is.na(glb_entity_df$<col1_name>), glb_entity_df$<col2_name>))
# print(table(sign(glb_entity_df$<col1_name>), glb_entity_df$<col2_name>))
# print(mycreate_xtab(glb_entity_df, <col1_name>))
# print(mycreate_xtab(glb_entity_df, c(<col1_name>, <col2_name>)))
# print(<col1_name>_<col2_name>_xtab_glb_entity_df <- 
#   mycreate_xtab(glb_entity_df, c("<col1_name>", "<col2_name>")))
# <col1_name>_<col2_name>_xtab_glb_entity_df[is.na(<col1_name>_<col2_name>_xtab_glb_entity_df)] <- 0
# print(<col1_name>_<col2_name>_xtab_glb_entity_df <- 
#   mutate(<col1_name>_<col2_name>_xtab_glb_entity_df, 
#             <col3_name>=(<col1_name> * 1.0) / (<col1_name> + <col2_name>))) 

# print(<col2_name>_min_entity_arr <- 
#    sort(tapply(glb_entity_df$<col1_name>, glb_entity_df$<col2_name>, min, na.rm=TRUE)))
# print(<col1_name>_na_by_<col2_name>_arr <- 
#    sort(tapply(glb_entity_df$<col1_name>.NA, glb_entity_df$<col2_name>, mean, na.rm=TRUE)))

# Other plots:
# print(myplot_box(df=glb_entity_df, ycol_names="<col1_name>"))
# print(myplot_box(df=glb_entity_df, ycol_names="<col1_name>", xcol_name="<col2_name>"))
# print(myplot_line(subset(glb_entity_df, Symbol %in% c("KO", "PG")), 
#                   "Date.my", "StockPrice", facet_row_colnames="Symbol") + 
#     geom_vline(xintercept=as.numeric(as.Date("2003-03-01"))) +
#     geom_vline(xintercept=as.numeric(as.Date("1983-01-01")))        
#         )
# print(myplot_scatter(glb_entity_df, "<col1_name>", "<col2_name>", smooth=TRUE))
# print(myplot_scatter(glb_entity_df, "<col1_name>", "<col2_name>", colorcol_name="<Pred.fctr>"))

glb_script_df <- rbind(glb_script_df, 
    data.frame(chunk_label="manage_missing_data", 
        chunk_step_major=max(glb_script_df$chunk_step_major), 
        chunk_step_minor=glb_script_df[nrow(glb_script_df), "chunk_step_minor"]+1,
                              elapsed=(proc.time() - glb_script_tm)["elapsed"]))
print(tail(glb_script_df, 2))
##                    chunk_label chunk_step_major chunk_step_minor elapsed
## elapsed2 inspectORexplore.data                2                1   6.707
## elapsed3   manage_missing_data                2                2   8.655

Step 2.2: manage missing data

# print(sapply(names(glb_entity_df), function(col) sum(is.na(glb_entity_df[, col]))))
# print(sapply(names(glb_newent_df), function(col) sum(is.na(glb_newent_df[, col]))))
# glb_entity_df <- na.omit(glb_entity_df)
# glb_newent_df <- na.omit(glb_newent_df)
# df[is.na(df)] <- 0

# Not refactored into mydsutils.R since glb_*_df might be reassigned
glb_impute_missing_data <- function(entity_df, newent_df) {
    if (!glb_is_separate_newent_dataset) {
        # Combine entity & newent
        union_df <- rbind(mutate(entity_df, .src = "entity"),
                          mutate(newent_df, .src = "newent"))
        union_imputed_df <- union_df[, setdiff(setdiff(names(entity_df), 
                                                       glb_rsp_var), 
                                               glb_exclude_vars_as_features)]
        print(summary(union_imputed_df))
    
        require(mice)
        set.seed(glb_mice_complete.seed)
        union_imputed_df <- complete(mice(union_imputed_df))
        print(summary(union_imputed_df))
    
        union_df[, names(union_imputed_df)] <- union_imputed_df[, names(union_imputed_df)]
        print(summary(union_df))
#         union_df$.rownames <- rownames(union_df)
#         union_df <- orderBy(~.rownames, union_df)
#         
#         imp_entity_df <- myimport_data(
#             url="<imputed_trnng_url>", 
#             comment="imp_entity_df", force_header=TRUE, print_diagn=TRUE)
#         print(all.equal(subset(union_df, select=-c(.src, .rownames, .rnorm)), 
#                         imp_entity_df))
        
        # Partition again
        glb_entity_df <<- subset(union_df, .src == "entity", select=-c(.src, .rownames))
        comment(glb_entity_df) <- "entity_df"
        glb_newent_df <<- subset(union_df, .src == "newent", select=-c(.src, .rownames))
        comment(glb_newent_df) <- "newent_df"
        
        # Generate summaries
        print(summary(entity_df))
        print(sapply(names(entity_df), function(col) sum(is.na(entity_df[, col]))))
        print(summary(newent_df))
        print(sapply(names(newent_df), function(col) sum(is.na(newent_df[, col]))))
    
    } else stop("Not implemented yet")
}

if (glb_impute_na_data) {
    if ((sum(sapply(names(glb_entity_df), 
                    function(col) sum(is.na(glb_entity_df[, col])))) > 0) | 
        (sum(sapply(names(glb_newent_df), 
                    function(col) sum(is.na(glb_newent_df[, col])))) > 0))
        glb_impute_missing_data(glb_entity_df, glb_newent_df)
}    

glb_script_df <- rbind(glb_script_df, 
    data.frame(chunk_label="encode_retype_data", 
        chunk_step_major=max(glb_script_df$chunk_step_major), 
        chunk_step_minor=glb_script_df[nrow(glb_script_df), "chunk_step_minor"]+1,
                              elapsed=(proc.time() - glb_script_tm)["elapsed"]))
print(tail(glb_script_df, 2))
##                  chunk_label chunk_step_major chunk_step_minor elapsed
## elapsed3 manage_missing_data                2                2   8.655
## elapsed4  encode_retype_data                2                3   9.057

Step 2.3: encode/retype data

# map_<col_name>_df <- myimport_data(
#     url="<map_url>", 
#     comment="map_<col_name>_df", print_diagn=TRUE)
# map_<col_name>_df <- read.csv(paste0(getwd(), "/data/<file_name>.csv"), strip.white=TRUE)

# glb_entity_df <- mymap_codes(glb_entity_df, "<from_col_name>", "<to_col_name>", 
#     map_<to_col_name>_df, map_join_col_name="<map_join_col_name>", 
#                           map_tgt_col_name="<to_col_name>")
# glb_newent_df <- mymap_codes(glb_newent_df, "<from_col_name>", "<to_col_name>", 
#     map_<to_col_name>_df, map_join_col_name="<map_join_col_name>", 
#                           map_tgt_col_name="<to_col_name>")
                        
# glb_entity_df$<col_name>.fctr <- factor(glb_entity_df$<col_name>, 
#                     as.factor(union(glb_entity_df$<col_name>, glb_newent_df$<col_name>)))
# glb_newent_df$<col_name>.fctr <- factor(glb_newent_df$<col_name>, 
#                     as.factor(union(glb_entity_df$<col_name>, glb_newent_df$<col_name>)))

if (!is.null(glb_map_rsp_raw_to_var)) {
    glb_entity_df[, glb_rsp_var] <- 
        glb_map_rsp_raw_to_var(glb_entity_df[, glb_rsp_var_raw])
    mycheck_map_results(mapd_df=glb_entity_df, 
                        from_col_name=glb_rsp_var_raw, to_col_name=glb_rsp_var)
        
    glb_newent_df[, glb_rsp_var] <- 
        glb_map_rsp_raw_to_var(glb_newent_df[, glb_rsp_var_raw])
    mycheck_map_results(mapd_df=glb_newent_df, 
                        from_col_name=glb_rsp_var_raw, to_col_name=glb_rsp_var)    

    glb_entity_df[, "bucket2008.fctr"] <- 
        glb_map_rsp_raw_to_var(glb_entity_df[, "bucket2008"])
    mycheck_map_results(mapd_df=glb_entity_df, 
                        from_col_name="bucket2008", to_col_name="bucket2008.fctr")
        
    glb_newent_df[, "bucket2008.fctr"] <- 
        glb_map_rsp_raw_to_var(glb_newent_df[, "bucket2008"])
    mycheck_map_results(mapd_df=glb_newent_df, 
                        from_col_name="bucket2008", to_col_name="bucket2008.fctr")    

}
## Loading required package: sqldf
## Loading required package: gsubfn
## Loading required package: proto
## Loading required package: RSQLite
## Loading required package: DBI
## Loading required package: tcltk
##   bucket2009 bucket2009.fctr    .n
## 1          1              B1 13426
## 2          2              B2  3803
## 3          3              B3  1789
## 4          4              B4   867
## 5          5              B5   115

##   bucket2009 bucket2009.fctr    .n
## 1          1              B1 13426
## 2          2              B2  3804
## 3          3              B3  1789
## 4          4              B4   866
## 5          5              B5   115

##   bucket2008 bucket2008.fctr    .n
## 1          1              B1 14896
## 2          2              B2  2731
## 3          3              B3  1324
## 4          4              B4   872
## 5          5              B5   177

##   bucket2008 bucket2008.fctr    .n
## 1          1              B1 14946
## 2          2              B2  2706
## 3          3              B3  1275
## 4          4              B4   905
## 5          5              B5   168

glb_script_df <- rbind(glb_script_df, 
                   data.frame(chunk_label="extract_features", 
                              chunk_step_major=max(glb_script_df$chunk_step_major)+1, 
                              chunk_step_minor=0,
                              elapsed=(proc.time() - glb_script_tm)["elapsed"]))
print(tail(glb_script_df, 2))
##                 chunk_label chunk_step_major chunk_step_minor elapsed
## elapsed4 encode_retype_data                2                3   9.057
## elapsed5   extract_features                3                0  14.307

Step 3: extract features

# Create new features that help prediction
# <col_name>.lag.2 <- lag(zoo(glb_entity_df$<col_name>), -2, na.pad=TRUE)
# glb_entity_df[, "<col_name>.lag.2"] <- coredata(<col_name>.lag.2)
# <col_name>.lag.2 <- lag(zoo(glb_newent_df$<col_name>), -2, na.pad=TRUE)
# glb_newent_df[, "<col_name>.lag.2"] <- coredata(<col_name>.lag.2)
# 
# glb_newent_df[1, "<col_name>.lag.2"] <- glb_entity_df[nrow(glb_entity_df) - 1, 
#                                                    "<col_name>"]
# glb_newent_df[2, "<col_name>.lag.2"] <- glb_entity_df[nrow(glb_entity_df), 
#                                                    "<col_name>"]
                                                   
# glb_entity_df <- mutate(glb_entity_df,
#     <new_col_name>=
#                     )

# glb_newent_df <- mutate(glb_newent_df,
#     <new_col_name>=
#                     )

# print(summary(glb_entity_df))
# print(summary(glb_newent_df))

# print(sapply(names(glb_entity_df), function(col) sum(is.na(glb_entity_df[, col]))))
# print(sapply(names(glb_newent_df), function(col) sum(is.na(glb_newent_df[, col]))))

# print(myplot_scatter(glb_entity_df, "<col1_name>", "<col2_name>", smooth=TRUE))

replay.petrisim(pn=glb_analytics_pn, 
    replay.trans=(glb_analytics_avl_objs <- c(glb_analytics_avl_objs, 
        "data.training.all","data.new")), flip_coord=TRUE)
## time trans    "bgn " "fit.data.training.all " "predict.data.new " "end " 
## 0.0000   multiple enabled transitions:  data.training.all data.new model.selected    firing:  data.training.all 
## 1.0000    1   2 1 0 0 
## 1.0000   multiple enabled transitions:  data.training.all data.new model.selected model.final data.training.all.prediction   firing:  data.new 
## 2.0000    2   1 1 1 0

glb_script_df <- rbind(glb_script_df, 
                   data.frame(chunk_label="select_features", 
                              chunk_step_major=max(glb_script_df$chunk_step_major)+1, 
                              chunk_step_minor=0,
                              elapsed=(proc.time() - glb_script_tm)["elapsed"]))
print(tail(glb_script_df, 2))
##               chunk_label chunk_step_major chunk_step_minor elapsed
## elapsed5 extract_features                3                0  14.307
## elapsed6  select_features                4                0  15.907

Step 4: select features

print(glb_feats_df <- myselect_features(entity_df=glb_entity_df, 
                       exclude_vars_as_features=glb_exclude_vars_as_features, 
                       rsp_var=glb_rsp_var))
##                                  id       cor.y exclude.as.feat  cor.y.abs
## bucket2009               bucket2009  1.00000000               1 1.00000000
## reimbursement2009 reimbursement2009  0.85935358               1 0.85935358
## bucket2008               bucket2008  0.44817654               0 0.44817654
## bucket2008.fctr     bucket2008.fctr  0.44817654               1 0.44817654
## diabetes                   diabetes  0.39573574               0 0.39573574
## ihd                             ihd  0.39279189               0 0.39279189
## reimbursement2008 reimbursement2008  0.37372205               0 0.37372205
## kidney                       kidney  0.37366230               0 0.37366230
## heart.failure         heart.failure  0.36422152               0 0.36422152
## copd                           copd  0.32033790               0 0.32033790
## depression               depression  0.28097857               0 0.28097857
## alzheimers               alzheimers  0.27426278               0 0.27426278
## arthritis                 arthritis  0.26626508               0 0.26626508
## osteoporosis           osteoporosis  0.20680648               0 0.20680648
## cancer                       cancer  0.19625387               0 0.19625387
## stroke                       stroke  0.18044011               0 0.18044011
## age                             age  0.04031166               0 0.04031166
## .rnorm                       .rnorm -0.01473661               0 0.01473661
glb_script_df <- rbind(glb_script_df, 
    data.frame(chunk_label="remove_correlated_features", 
        chunk_step_major=max(glb_script_df$chunk_step_major),
        chunk_step_minor=glb_script_df[nrow(glb_script_df), "chunk_step_minor"]+1,
                              elapsed=(proc.time() - glb_script_tm)["elapsed"]))        
print(tail(glb_script_df, 2))
##                         chunk_label chunk_step_major chunk_step_minor
## elapsed6            select_features                4                0
## elapsed7 remove_correlated_features                4                1
##          elapsed
## elapsed6  15.907
## elapsed7  16.231

Step 4.1: remove correlated features

print(glb_feats_df <- orderBy(~-cor.y, 
          myfind_cor_features(feats_df=glb_feats_df, entity_df=glb_entity_df, 
                                rsp_var=glb_rsp_var)))
## Loading required package: reshape2
##                     bucket2008     diabetes         ihd reimbursement2008
## bucket2008         1.000000000  0.447914565 0.456763211       0.848409759
## diabetes           0.447914565  1.000000000 0.506214450       0.356346675
## ihd                0.456763211  0.506214450 1.000000000       0.359791577
## reimbursement2008  0.848409759  0.356346675 0.359791577       1.000000000
## kidney             0.550020556  0.412720314 0.377863565       0.472203943
## heart.failure      0.481538139  0.446054842 0.462970200       0.395066334
## copd               0.486160585  0.328963733 0.347336535       0.416038942
## depression         0.337024534  0.354038559 0.322851158       0.272843989
## alzheimers         0.363340178  0.338226128 0.327500830       0.302558840
## arthritis          0.319151481  0.320741293 0.306246996       0.250877445
## osteoporosis       0.231165834  0.274883805 0.264198008       0.176071649
## cancer             0.290037692  0.177350541 0.192964189       0.238438967
## stroke             0.321249903  0.185957449 0.190210708       0.289233604
## age                0.064193842  0.059141813 0.057644660       0.042244569
## .rnorm            -0.007437985 -0.004198605 0.002868762      -0.006238027
##                         kidney heart.failure         copd   depression
## bucket2008         0.550020556   0.481538139  0.486160585  0.337024534
## diabetes           0.412720314   0.446054842  0.328963733  0.354038559
## ihd                0.377863565   0.462970200  0.347336535  0.322851158
## reimbursement2008  0.472203943   0.395066334  0.416038942  0.272843989
## kidney             1.000000000   0.418629559  0.364003865  0.272097169
## heart.failure      0.418629559   1.000000000  0.372766807  0.302889845
## copd               0.364003865   0.372766807  1.000000000  0.243096772
## depression         0.272097169   0.302889845  0.243096772  1.000000000
## alzheimers         0.300392086   0.310663583  0.272968595  0.278223947
## arthritis          0.246302237   0.261393477  0.210780691  0.230017166
## osteoporosis       0.196737654   0.223182861  0.185876087  0.199100341
## cancer             0.176011818   0.164149799  0.167571990  0.125219898
## stroke             0.218701272   0.218931513  0.197104631  0.151495349
## age                0.055489575   0.063915389  0.039260002  0.006119113
## .rnorm            -0.001055755  -0.009117947 -0.001951984 -0.010865386
##                    alzheimers   arthritis osteoporosis      cancer
## bucket2008         0.36334018 0.319151481  0.231165834 0.290037692
## diabetes           0.33822613 0.320741293  0.274883805 0.177350541
## ihd                0.32750083 0.306246996  0.264198008 0.192964189
## reimbursement2008  0.30255884 0.250877445  0.176071649 0.238438967
## kidney             0.30039209 0.246302237  0.196737654 0.176011818
## heart.failure      0.31066358 0.261393477  0.223182861 0.164149799
## copd               0.27296860 0.210780691  0.185876087 0.167571990
## depression         0.27822395 0.230017166  0.199100341 0.125219898
## alzheimers         1.00000000 0.209905302  0.181189485 0.136980587
## arthritis          0.20990530 1.000000000  0.226901017 0.107465454
## osteoporosis       0.18118949 0.226901017  1.000000000 0.112035767
## cancer             0.13698059 0.107465454  0.112035767 1.000000000
## stroke             0.21027859 0.119552004  0.093017408 0.080214960
## age                0.04052059 0.036432382  0.030826027 0.033020629
## .rnorm            -0.01058946 0.002960374  0.008788716 0.006577402
##                         stroke          age       .rnorm
## bucket2008         0.321249903  0.064193842 -0.007437985
## diabetes           0.185957449  0.059141813 -0.004198605
## ihd                0.190210708  0.057644660  0.002868762
## reimbursement2008  0.289233604  0.042244569 -0.006238027
## kidney             0.218701272  0.055489575 -0.001055755
## heart.failure      0.218931513  0.063915389 -0.009117947
## copd               0.197104631  0.039260002 -0.001951984
## depression         0.151495349  0.006119113 -0.010865386
## alzheimers         0.210278592  0.040520594 -0.010589458
## arthritis          0.119552004  0.036432382  0.002960374
## osteoporosis       0.093017408  0.030826027  0.008788716
## cancer             0.080214960  0.033020629  0.006577402
## stroke             1.000000000  0.041366912 -0.003176158
## age                0.041366912  1.000000000 -0.011909736
## .rnorm            -0.003176158 -0.011909736  1.000000000
##                    bucket2008    diabetes         ihd reimbursement2008
## bucket2008        0.000000000 0.447914565 0.456763211       0.848409759
## diabetes          0.447914565 0.000000000 0.506214450       0.356346675
## ihd               0.456763211 0.506214450 0.000000000       0.359791577
## reimbursement2008 0.848409759 0.356346675 0.359791577       0.000000000
## kidney            0.550020556 0.412720314 0.377863565       0.472203943
## heart.failure     0.481538139 0.446054842 0.462970200       0.395066334
## copd              0.486160585 0.328963733 0.347336535       0.416038942
## depression        0.337024534 0.354038559 0.322851158       0.272843989
## alzheimers        0.363340178 0.338226128 0.327500830       0.302558840
## arthritis         0.319151481 0.320741293 0.306246996       0.250877445
## osteoporosis      0.231165834 0.274883805 0.264198008       0.176071649
## cancer            0.290037692 0.177350541 0.192964189       0.238438967
## stroke            0.321249903 0.185957449 0.190210708       0.289233604
## age               0.064193842 0.059141813 0.057644660       0.042244569
## .rnorm            0.007437985 0.004198605 0.002868762       0.006238027
##                        kidney heart.failure        copd  depression
## bucket2008        0.550020556   0.481538139 0.486160585 0.337024534
## diabetes          0.412720314   0.446054842 0.328963733 0.354038559
## ihd               0.377863565   0.462970200 0.347336535 0.322851158
## reimbursement2008 0.472203943   0.395066334 0.416038942 0.272843989
## kidney            0.000000000   0.418629559 0.364003865 0.272097169
## heart.failure     0.418629559   0.000000000 0.372766807 0.302889845
## copd              0.364003865   0.372766807 0.000000000 0.243096772
## depression        0.272097169   0.302889845 0.243096772 0.000000000
## alzheimers        0.300392086   0.310663583 0.272968595 0.278223947
## arthritis         0.246302237   0.261393477 0.210780691 0.230017166
## osteoporosis      0.196737654   0.223182861 0.185876087 0.199100341
## cancer            0.176011818   0.164149799 0.167571990 0.125219898
## stroke            0.218701272   0.218931513 0.197104631 0.151495349
## age               0.055489575   0.063915389 0.039260002 0.006119113
## .rnorm            0.001055755   0.009117947 0.001951984 0.010865386
##                   alzheimers   arthritis osteoporosis      cancer
## bucket2008        0.36334018 0.319151481  0.231165834 0.290037692
## diabetes          0.33822613 0.320741293  0.274883805 0.177350541
## ihd               0.32750083 0.306246996  0.264198008 0.192964189
## reimbursement2008 0.30255884 0.250877445  0.176071649 0.238438967
## kidney            0.30039209 0.246302237  0.196737654 0.176011818
## heart.failure     0.31066358 0.261393477  0.223182861 0.164149799
## copd              0.27296860 0.210780691  0.185876087 0.167571990
## depression        0.27822395 0.230017166  0.199100341 0.125219898
## alzheimers        0.00000000 0.209905302  0.181189485 0.136980587
## arthritis         0.20990530 0.000000000  0.226901017 0.107465454
## osteoporosis      0.18118949 0.226901017  0.000000000 0.112035767
## cancer            0.13698059 0.107465454  0.112035767 0.000000000
## stroke            0.21027859 0.119552004  0.093017408 0.080214960
## age               0.04052059 0.036432382  0.030826027 0.033020629
## .rnorm            0.01058946 0.002960374  0.008788716 0.006577402
##                        stroke         age      .rnorm
## bucket2008        0.321249903 0.064193842 0.007437985
## diabetes          0.185957449 0.059141813 0.004198605
## ihd               0.190210708 0.057644660 0.002868762
## reimbursement2008 0.289233604 0.042244569 0.006238027
## kidney            0.218701272 0.055489575 0.001055755
## heart.failure     0.218931513 0.063915389 0.009117947
## copd              0.197104631 0.039260002 0.001951984
## depression        0.151495349 0.006119113 0.010865386
## alzheimers        0.210278592 0.040520594 0.010589458
## arthritis         0.119552004 0.036432382 0.002960374
## osteoporosis      0.093017408 0.030826027 0.008788716
## cancer            0.080214960 0.033020629 0.006577402
## stroke            0.000000000 0.041366912 0.003176158
## age               0.041366912 0.000000000 0.011909736
## .rnorm            0.003176158 0.011909736 0.000000000
## [1] "cor(bucket2008, reimbursement2008)=0.8484"

## [1] "cor(bucket2009.fctr, bucket2008)=0.4482"
## [1] "cor(bucket2009.fctr, reimbursement2008)=0.3737"
## geom_smooth: Only one unique x value each group.Maybe you want aes(group = 1)?
## geom_smooth: Only one unique x value each group.Maybe you want aes(group = 1)?
## geom_smooth: Only one unique x value each group.Maybe you want aes(group = 1)?
## geom_smooth: Only one unique x value each group.Maybe you want aes(group = 1)?
## Warning in myfind_cor_features(feats_df = glb_feats_df, entity_df =
## glb_entity_df, : Identified reimbursement2008 as highly correlated with
## other features

## [1] "checking correlations for features:"
##  [1] "bucket2008"    "diabetes"      "ihd"           "kidney"       
##  [5] "heart.failure" "copd"          "depression"    "alzheimers"   
##  [9] "arthritis"     "osteoporosis"  "cancer"        "stroke"       
## [13] "age"           ".rnorm"       
##                 bucket2008     diabetes         ihd       kidney
## bucket2008     1.000000000  0.447914565 0.456763211  0.550020556
## diabetes       0.447914565  1.000000000 0.506214450  0.412720314
## ihd            0.456763211  0.506214450 1.000000000  0.377863565
## kidney         0.550020556  0.412720314 0.377863565  1.000000000
## heart.failure  0.481538139  0.446054842 0.462970200  0.418629559
## copd           0.486160585  0.328963733 0.347336535  0.364003865
## depression     0.337024534  0.354038559 0.322851158  0.272097169
## alzheimers     0.363340178  0.338226128 0.327500830  0.300392086
## arthritis      0.319151481  0.320741293 0.306246996  0.246302237
## osteoporosis   0.231165834  0.274883805 0.264198008  0.196737654
## cancer         0.290037692  0.177350541 0.192964189  0.176011818
## stroke         0.321249903  0.185957449 0.190210708  0.218701272
## age            0.064193842  0.059141813 0.057644660  0.055489575
## .rnorm        -0.007437985 -0.004198605 0.002868762 -0.001055755
##               heart.failure         copd   depression  alzheimers
## bucket2008      0.481538139  0.486160585  0.337024534  0.36334018
## diabetes        0.446054842  0.328963733  0.354038559  0.33822613
## ihd             0.462970200  0.347336535  0.322851158  0.32750083
## kidney          0.418629559  0.364003865  0.272097169  0.30039209
## heart.failure   1.000000000  0.372766807  0.302889845  0.31066358
## copd            0.372766807  1.000000000  0.243096772  0.27296860
## depression      0.302889845  0.243096772  1.000000000  0.27822395
## alzheimers      0.310663583  0.272968595  0.278223947  1.00000000
## arthritis       0.261393477  0.210780691  0.230017166  0.20990530
## osteoporosis    0.223182861  0.185876087  0.199100341  0.18118949
## cancer          0.164149799  0.167571990  0.125219898  0.13698059
## stroke          0.218931513  0.197104631  0.151495349  0.21027859
## age             0.063915389  0.039260002  0.006119113  0.04052059
## .rnorm         -0.009117947 -0.001951984 -0.010865386 -0.01058946
##                 arthritis osteoporosis      cancer       stroke
## bucket2008    0.319151481  0.231165834 0.290037692  0.321249903
## diabetes      0.320741293  0.274883805 0.177350541  0.185957449
## ihd           0.306246996  0.264198008 0.192964189  0.190210708
## kidney        0.246302237  0.196737654 0.176011818  0.218701272
## heart.failure 0.261393477  0.223182861 0.164149799  0.218931513
## copd          0.210780691  0.185876087 0.167571990  0.197104631
## depression    0.230017166  0.199100341 0.125219898  0.151495349
## alzheimers    0.209905302  0.181189485 0.136980587  0.210278592
## arthritis     1.000000000  0.226901017 0.107465454  0.119552004
## osteoporosis  0.226901017  1.000000000 0.112035767  0.093017408
## cancer        0.107465454  0.112035767 1.000000000  0.080214960
## stroke        0.119552004  0.093017408 0.080214960  1.000000000
## age           0.036432382  0.030826027 0.033020629  0.041366912
## .rnorm        0.002960374  0.008788716 0.006577402 -0.003176158
##                        age       .rnorm
## bucket2008     0.064193842 -0.007437985
## diabetes       0.059141813 -0.004198605
## ihd            0.057644660  0.002868762
## kidney         0.055489575 -0.001055755
## heart.failure  0.063915389 -0.009117947
## copd           0.039260002 -0.001951984
## depression     0.006119113 -0.010865386
## alzheimers     0.040520594 -0.010589458
## arthritis      0.036432382  0.002960374
## osteoporosis   0.030826027  0.008788716
## cancer         0.033020629  0.006577402
## stroke         0.041366912 -0.003176158
## age            1.000000000 -0.011909736
## .rnorm        -0.011909736  1.000000000
##                bucket2008    diabetes         ihd      kidney
## bucket2008    0.000000000 0.447914565 0.456763211 0.550020556
## diabetes      0.447914565 0.000000000 0.506214450 0.412720314
## ihd           0.456763211 0.506214450 0.000000000 0.377863565
## kidney        0.550020556 0.412720314 0.377863565 0.000000000
## heart.failure 0.481538139 0.446054842 0.462970200 0.418629559
## copd          0.486160585 0.328963733 0.347336535 0.364003865
## depression    0.337024534 0.354038559 0.322851158 0.272097169
## alzheimers    0.363340178 0.338226128 0.327500830 0.300392086
## arthritis     0.319151481 0.320741293 0.306246996 0.246302237
## osteoporosis  0.231165834 0.274883805 0.264198008 0.196737654
## cancer        0.290037692 0.177350541 0.192964189 0.176011818
## stroke        0.321249903 0.185957449 0.190210708 0.218701272
## age           0.064193842 0.059141813 0.057644660 0.055489575
## .rnorm        0.007437985 0.004198605 0.002868762 0.001055755
##               heart.failure        copd  depression alzheimers   arthritis
## bucket2008      0.481538139 0.486160585 0.337024534 0.36334018 0.319151481
## diabetes        0.446054842 0.328963733 0.354038559 0.33822613 0.320741293
## ihd             0.462970200 0.347336535 0.322851158 0.32750083 0.306246996
## kidney          0.418629559 0.364003865 0.272097169 0.30039209 0.246302237
## heart.failure   0.000000000 0.372766807 0.302889845 0.31066358 0.261393477
## copd            0.372766807 0.000000000 0.243096772 0.27296860 0.210780691
## depression      0.302889845 0.243096772 0.000000000 0.27822395 0.230017166
## alzheimers      0.310663583 0.272968595 0.278223947 0.00000000 0.209905302
## arthritis       0.261393477 0.210780691 0.230017166 0.20990530 0.000000000
## osteoporosis    0.223182861 0.185876087 0.199100341 0.18118949 0.226901017
## cancer          0.164149799 0.167571990 0.125219898 0.13698059 0.107465454
## stroke          0.218931513 0.197104631 0.151495349 0.21027859 0.119552004
## age             0.063915389 0.039260002 0.006119113 0.04052059 0.036432382
## .rnorm          0.009117947 0.001951984 0.010865386 0.01058946 0.002960374
##               osteoporosis      cancer      stroke         age      .rnorm
## bucket2008     0.231165834 0.290037692 0.321249903 0.064193842 0.007437985
## diabetes       0.274883805 0.177350541 0.185957449 0.059141813 0.004198605
## ihd            0.264198008 0.192964189 0.190210708 0.057644660 0.002868762
## kidney         0.196737654 0.176011818 0.218701272 0.055489575 0.001055755
## heart.failure  0.223182861 0.164149799 0.218931513 0.063915389 0.009117947
## copd           0.185876087 0.167571990 0.197104631 0.039260002 0.001951984
## depression     0.199100341 0.125219898 0.151495349 0.006119113 0.010865386
## alzheimers     0.181189485 0.136980587 0.210278592 0.040520594 0.010589458
## arthritis      0.226901017 0.107465454 0.119552004 0.036432382 0.002960374
## osteoporosis   0.000000000 0.112035767 0.093017408 0.030826027 0.008788716
## cancer         0.112035767 0.000000000 0.080214960 0.033020629 0.006577402
## stroke         0.093017408 0.080214960 0.000000000 0.041366912 0.003176158
## age            0.030826027 0.033020629 0.041366912 0.000000000 0.011909736
## .rnorm         0.008788716 0.006577402 0.003176158 0.011909736 0.000000000
##                                  id       cor.y exclude.as.feat  cor.y.abs
## bucket2009               bucket2009  1.00000000               1 1.00000000
## reimbursement2009 reimbursement2009  0.85935358               1 0.85935358
## bucket2008               bucket2008  0.44817654               0 0.44817654
## bucket2008.fctr     bucket2008.fctr  0.44817654               1 0.44817654
## diabetes                   diabetes  0.39573574               0 0.39573574
## ihd                             ihd  0.39279189               0 0.39279189
## reimbursement2008 reimbursement2008  0.37372205               0 0.37372205
## kidney                       kidney  0.37366230               0 0.37366230
## heart.failure         heart.failure  0.36422152               0 0.36422152
## copd                           copd  0.32033790               0 0.32033790
## depression               depression  0.28097857               0 0.28097857
## alzheimers               alzheimers  0.27426278               0 0.27426278
## arthritis                 arthritis  0.26626508               0 0.26626508
## osteoporosis           osteoporosis  0.20680648               0 0.20680648
## cancer                       cancer  0.19625387               0 0.19625387
## stroke                       stroke  0.18044011               0 0.18044011
## age                             age  0.04031166               0 0.04031166
## .rnorm                       .rnorm -0.01473661               0 0.01473661
##                   cor.low
## bucket2009              0
## reimbursement2009       0
## bucket2008              1
## bucket2008.fctr         0
## diabetes                1
## ihd                     1
## reimbursement2008       0
## kidney                  1
## heart.failure           1
## copd                    1
## depression              1
## alzheimers              1
## arthritis               1
## osteoporosis            1
## cancer                  1
## stroke                  1
## age                     1
## .rnorm                  1
glb_script_df <- rbind(glb_script_df, 
                   data.frame(chunk_label="fit.models", 
                              chunk_step_major=max(glb_script_df$chunk_step_major)+1, 
                              chunk_step_minor=0,
                              elapsed=(proc.time() - glb_script_tm)["elapsed"]))
print(tail(glb_script_df, 2))
##                         chunk_label chunk_step_major chunk_step_minor
## elapsed7 remove_correlated_features                4                1
## elapsed8                 fit.models                5                0
##          elapsed
## elapsed7  16.231
## elapsed8  19.860

Step 5: fit models

max_cor_y_x_var <- subset(glb_feats_df, cor.low == 1)[1, "id"]
if (!is.null(glb_Baseline_mdl_var)) {
    if ((max_cor_y_x_var != glb_Baseline_mdl_var) & 
        (glb_feats_df[max_cor_y_x_var, "cor.y.abs"] > 
         glb_feats_df[glb_Baseline_mdl_var, "cor.y.abs"]))
        stop(max_cor_y_x_var, " has a lower correlation with ", glb_rsp_var, 
             " than the Baseline var: ", glb_Baseline_mdl_var)
}

#   Regression:
if (glb_is_regression) {
    #   Linear:
    myfit_mdl_fn <- myfit_mdl_lm
}    

#   Classification:
if (glb_is_classification) myfit_mdl_fn <- myfit_mdl_classification 
glb_is_binomial <- (length(unique(glb_entity_df[, glb_rsp_var])) <= 2)

# Any models that have tuning parameters has "better" results with cross-validation
#   & "different" results for different outcome metrics

# Baseline
if (!is.null(glb_Baseline_mdl_var)) {
#     lm_mdl <- lm(reformulate(glb_Baseline_mdl_var, 
#                             response="bucket2009"), data=glb_entity_df)
#     print(summary(lm_mdl))
#     plot(lm_mdl, ask=FALSE)
#     ret_lst <- myfit_mdl_fn(model_id="Baseline", 
#                             model_method=ifelse(glb_is_regression, "lm", 
#                                         ifelse(glb_is_binomial, "glm", "rpart")),
#                             indep_vars_vctr=glb_Baseline_mdl_var,
#                             rsp_var=glb_rsp_var, rsp_var_out=glb_rsp_var_out,
#                             fit_df=glb_entity_df, OOB_df=glb_newent_df,
#                             n_cv_folds=0, tune_models_df=NULL,
#                             model_loss_mtrx=glb_model_metric_terms,
#                             model_summaryFunction=glb_model_metric_smmry,
#                             model_metric=glb_model_metric,
#                             model_metric_maximize=glb_model_metric_maximize)
    ret_lst <- myfit_mdl_fn(model_id="Baseline", model_method="mybaseln_classfr",
                            indep_vars_vctr=glb_Baseline_mdl_var,
                            rsp_var=glb_rsp_var, rsp_var_out=glb_rsp_var_out,
                            fit_df=glb_entity_df, OOB_df=glb_newent_df)
}
## Loading required package: caret
## Loading required package: lattice
## 
## Attaching package: 'caret'
## 
## The following object is masked from 'package:survival':
## 
##     cluster
## [1] "fitting model: Baseline.mybaseln_classfr"
## [1] "    indep_vars: bucket2008.fctr, .rnorm"
## Fitting parameter = none on full training set
## [1] "in Baseline.Classifier$fit"
## [1] "class(x):"
## [1] "matrix"
## [1] "dimnames(x)[[2]]:"
## [1] "bucket2008.fctrB2" "bucket2008.fctrB3" "bucket2008.fctrB4"
## [4] "bucket2008.fctrB5" ".rnorm"           
## [1] "length(x):"
## [1] 100000
## [1] "head(x):"
##     bucket2008.fctrB2 bucket2008.fctrB3 bucket2008.fctrB4
## 15                  0                 0                 0
## 17                  0                 0                 0
## 48                  0                 0                 0
## 82                  0                 0                 0
## 170                 0                 0                 0
## 199                 0                 0                 0
##     bucket2008.fctrB5      .rnorm
## 15                  0  0.03766206
## 17                  0  1.07112991
## 48                  0 -2.13144213
## 82                  0 -1.08526226
## 170                 0 -0.20923275
## 199                 0 -0.17566037
## [1] "class(y):"
## [1] "factor"
## [1] "length(y):"
## [1] 20000
## [1] "head(y):"
##  15  17  48  82 170 199 
##  B1  B1  B1  B1  B1  B1 
## Levels: B1 B2 B3 B4 B5
##             Length Class      Mode     
## x_names     4      -none-     character
## x_vals      5      -none-     character
## xNames      5      -none-     character
## problemType 1      -none-     character
## tuneValue   1      data.frame list     
## obsLevels   5      -none-     character
## [1] "in Baseline.Classifier$predict"
## [1] "class(newdata):"
## [1] "matrix"
## [1] "head(newdata):"
##     bucket2008.fctrB2 bucket2008.fctrB3 bucket2008.fctrB4
## 15                  0                 0                 0
## 17                  0                 0                 0
## 48                  0                 0                 0
## 82                  0                 0                 0
## 170                 0                 0                 0
## 199                 0                 0                 0
##     bucket2008.fctrB5      .rnorm
## 15                  0  0.03766206
## 17                  0  1.07112991
## 48                  0 -2.13144213
## 82                  0 -1.08526226
## 170                 0 -0.20923275
## 199                 0 -0.17566037
## [1] "x_names: "
## [1] "bucket2008.fctrB2" "bucket2008.fctrB3" "bucket2008.fctrB4"
## [4] "bucket2008.fctrB5"
## [1] "x_vals: "
## [1] "B1" "B2" "B3" "B4" "B5"
## [1] "length(y):"
## [1] 20000
## [1] "head(y):"
## [1] B1 B1 B1 B1 B1 B1
## Levels: B1 B2 B3 B4 B5
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12003   869   372   158    24
##        B2  1774  1151   489   326    63
##        B3   797   494   276   178    44
##        B4   289   199   165   176    38
##        B5    33    18    22    34     8
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   6.807000e-01   3.150835e-01   6.741879e-01   6.871595e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   2.337804e-03  1.254477e-115 
## [1] "in Baseline.Classifier$predict"
## [1] "class(newdata):"
## [1] "matrix"
## [1] "head(newdata):"
##    bucket2008.fctrB2 bucket2008.fctrB3 bucket2008.fctrB4 bucket2008.fctrB5
## 5                  0                 0                 0                 0
## 25                 0                 0                 0                 0
## 38                 0                 0                 0                 0
## 60                 0                 0                 0                 0
## 69                 0                 0                 0                 0
## 83                 0                 0                 0                 0
##        .rnorm
## 5   0.2563804
## 25  1.2084722
## 38  0.6426727
## 60  0.6402416
## 69 -0.7905369
## 83  0.3301544
## [1] "x_names: "
## [1] "bucket2008.fctrB2" "bucket2008.fctrB3" "bucket2008.fctrB4"
## [4] "bucket2008.fctrB5"
## [1] "x_vals: "
## [1] "B1" "B2" "B3" "B4" "B5"
## [1] "length(y):"
## [1] 20000
## [1] "head(y):"
## [1] B1 B1 B1 B1 B1 B1
## Levels: B1 B2 B3 B4 B5
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12059   840   355   155    17
##        B2  1775  1160   476   337    56
##        B3   782   494   284   188    41
##        B4   296   196   144   189    41
##        B5    34    16    16    36    13
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   6.852500e-01   3.229631e-01   6.787621e-01   6.916841e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   1.294059e-05  4.571070e-127 
##                    model_id     model_method                   feats
## 1 Baseline.mybaseln_classfr mybaseln_classfr bucket2008.fctr, .rnorm
##   max.nTuningRuns min.elapsedtime.everything min.elapsedtime.final
## 1               0                      0.425                 0.003
##   max.Accuracy.fit max.AccuracyLower.fit max.AccuracyUpper.fit
## 1           0.6807             0.6741879             0.6871595
##   max.Kappa.fit max.Accuracy.OOB max.AccuracyLower.OOB
## 1     0.3150835          0.68525             0.6787621
##   max.AccuracyUpper.OOB max.Kappa.OOB min.SSE.fit
## 1             0.6916841     0.3229631           0
# Most Frequent Outcome "MFO" model: mean(y) for regression
#   Not using caret's nullModel since model stats not avl
#   Cannot use rpart for multinomial classification since it predicts non-MFO
ret_lst <- myfit_mdl_fn(model_id="MFO", model_method="myMFO_classfr",
                        indep_vars_vctr=".rnorm",
                        rsp_var=glb_rsp_var, rsp_var_out=glb_rsp_var_out,
                        fit_df=glb_entity_df, OOB_df=glb_newent_df)
## [1] "fitting model: MFO.myMFO_classfr"
## [1] "    indep_vars: .rnorm"
## Fitting parameter = none on full training set
## [1] "in MFO.Classifier$fit"
## [1] "unique.vals:"
## [1] B1 B2 B3 B4 B5
## Levels: B1 B2 B3 B4 B5
## [1] "unique.prob:"
## y
##      B1      B2      B3      B4      B5 
## 0.67130 0.19015 0.08945 0.04335 0.00575 
## [1] "MFO.val:"
## [1] "B1"
##             Length Class      Mode     
## unique.vals 5      factor     numeric  
## unique.prob 5      -none-     numeric  
## MFO.val     1      -none-     character
## xNames      1      -none-     character
## problemType 1      -none-     character
## tuneValue   1      data.frame list     
## obsLevels   5      -none-     character
## [1] "in MFO.Classifier$predict"
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 13426     0     0     0     0
##        B2  3803     0     0     0     0
##        B3  1789     0     0     0     0
##        B4   867     0     0     0     0
##        B5   115     0     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##      0.6713000      0.0000000      0.6647403      0.6778099      0.6713000 
## AccuracyPValue  McnemarPValue 
##      0.5033455            NaN 
## [1] "in MFO.Classifier$predict"
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 13426     0     0     0     0
##        B2  3804     0     0     0     0
##        B3  1789     0     0     0     0
##        B4   866     0     0     0     0
##        B5   115     0     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##      0.6713000      0.0000000      0.6647403      0.6778099      0.6713000 
## AccuracyPValue  McnemarPValue 
##      0.5033455            NaN 
##            model_id  model_method  feats max.nTuningRuns
## 1 MFO.myMFO_classfr myMFO_classfr .rnorm               0
##   min.elapsedtime.everything min.elapsedtime.final max.Accuracy.fit
## 1                      0.258                 0.005           0.6713
##   max.AccuracyLower.fit max.AccuracyUpper.fit max.Kappa.fit
## 1             0.6647403             0.6778099             0
##   max.Accuracy.OOB max.AccuracyLower.OOB max.AccuracyUpper.OOB
## 1           0.6713             0.6647403             0.6778099
##   max.Kappa.OOB min.SSE.fit
## 1             0           0
# "random" model - only for classification; none needed for regression since it is same as MFO
ret_lst <- myfit_mdl_fn(model_id="Random", model_method="myrandom_classfr",
                        indep_vars_vctr=".rnorm",
                        rsp_var=glb_rsp_var, rsp_var_out=glb_rsp_var_out,
                        fit_df=glb_entity_df, OOB_df=glb_newent_df)
## [1] "fitting model: Random.myrandom_classfr"
## [1] "    indep_vars: .rnorm"
## Fitting parameter = none on full training set
##             Length Class      Mode     
## unique.vals 5      factor     numeric  
## unique.prob 5      table      numeric  
## xNames      1      -none-     character
## problemType 1      -none-     character
## tuneValue   1      data.frame list     
## obsLevels   5      -none-     character
##          Prediction
## Reference   B1   B2   B3   B4   B5
##        B1 9045 2543 1187  574   77
##        B2 2567  701  342  175   18
##        B3 1211  327  164   79    8
##        B4  573  168   77   46    3
##        B5   75   26    7    7    0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   4.978000e-01  -7.473179e-05   4.908463e-01   5.047543e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   1.000000e+00   9.470695e-01 
##          Prediction
## Reference   B1   B2   B3   B4   B5
##        B1 9030 2583 1181  562   70
##        B2 2515  755  321  196   17
##        B3 1217  346  144   73    9
##        B4  600  144   69   50    3
##        B5   73   24   13    4    1
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##    0.499000000    0.003477783    0.492046063    0.505954228    0.671300000 
## AccuracyPValue  McnemarPValue 
##    1.000000000    0.181314260 
##                  model_id     model_method  feats max.nTuningRuns
## 1 Random.myrandom_classfr myrandom_classfr .rnorm               0
##   min.elapsedtime.everything min.elapsedtime.final max.Accuracy.fit
## 1                      0.231                 0.003           0.4978
##   max.AccuracyLower.fit max.AccuracyUpper.fit max.Kappa.fit
## 1             0.4908463             0.5047543 -7.473179e-05
##   max.Accuracy.OOB max.AccuracyLower.OOB max.AccuracyUpper.OOB
## 1            0.499             0.4920461             0.5059542
##   max.Kappa.OOB min.SSE.fit
## 1   0.003477783           0
# Max.cor.Y
ret_lst <- myfit_mdl_fn(model_id="Max.cor.Y.cv.0", 
                        model_method=ifelse(glb_is_regression, "lm", 
                                        ifelse(glb_is_binomial, "glm", "rpart")),
                        indep_vars_vctr=max_cor_y_x_var,
                        rsp_var=glb_rsp_var, rsp_var_out=glb_rsp_var_out,
                        fit_df=glb_entity_df, OOB_df=glb_newent_df)
## [1] "fitting model: Max.cor.Y.cv.0.rpart"
## [1] "    indep_vars: bucket2008"
## Loading required package: rpart
## Fitting cp = 0.0922 on full training set
## Loading required package: rpart.plot

## Call:
## rpart(formula = .outcome ~ ., control = list(minsplit = 20, minbucket = 7, 
##     cp = 0, maxcompete = 4, maxsurrogate = 5, usesurrogate = 2, 
##     surrogatestyle = 0, maxdepth = 30, xval = 0))
##   n= 20000 
## 
##           CP nsplit rel error
## 1 0.09218132      0         1
## 
## Node number 1: 20000 observations
##   predicted class=B1  expected loss=0.3287  P(node) =1
##     class counts: 13426  3803  1789   867   115
##    probabilities: 0.671 0.190 0.089 0.043 0.006 
## 
## n= 20000 
## 
## node), split, n, loss, yval, (yprob)
##       * denotes terminal node
## 
## 1) root 20000 6574 B1 (0.67 0.19 0.089 0.043 0.0057) *
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 13426     0     0     0     0
##        B2  3803     0     0     0     0
##        B3  1789     0     0     0     0
##        B4   867     0     0     0     0
##        B5   115     0     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##      0.6713000      0.0000000      0.6647403      0.6778099      0.6713000 
## AccuracyPValue  McnemarPValue 
##      0.5033455            NaN 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 13426     0     0     0     0
##        B2  3804     0     0     0     0
##        B3  1789     0     0     0     0
##        B4   866     0     0     0     0
##        B5   115     0     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##      0.6713000      0.0000000      0.6647403      0.6778099      0.6713000 
## AccuracyPValue  McnemarPValue 
##      0.5033455            NaN 
##               model_id model_method      feats max.nTuningRuns
## 1 Max.cor.Y.cv.0.rpart        rpart bucket2008               0
##   min.elapsedtime.everything min.elapsedtime.final max.Accuracy.fit
## 1                      0.779                 0.248           0.6713
##   max.AccuracyLower.fit max.AccuracyUpper.fit max.Kappa.fit
## 1             0.6647403             0.6778099             0
##   max.Accuracy.OOB max.AccuracyLower.OOB max.AccuracyUpper.OOB
## 1           0.6713             0.6647403             0.6778099
##   max.Kappa.OOB min.SSE.fit
## 1             0           0
ret_lst <- myfit_mdl_fn(model_id="Max.cor.Y.cv.G", 
                        model_method=ifelse(glb_is_regression, "lm", 
                                        ifelse(glb_is_binomial, "glm", "rpart")),
                        indep_vars_vctr=max_cor_y_x_var,
                        rsp_var=glb_rsp_var, rsp_var_out=glb_rsp_var_out,
                        fit_df=glb_entity_df, OOB_df=glb_newent_df,
                        n_cv_folds=glb_n_cv_folds, tune_models_df=NULL)
## [1] "fitting model: Max.cor.Y.cv.G.rpart"
## [1] "    indep_vars: bucket2008"
## + Fold1: cp=0 
## - Fold1: cp=0 
## + Fold2: cp=0 
## - Fold2: cp=0 
## + Fold3: cp=0 
## - Fold3: cp=0 
## + Fold4: cp=0 
## - Fold4: cp=0 
## + Fold5: cp=0 
## - Fold5: cp=0 
## Aggregating results
## Selecting tuning parameters
## Fitting cp = 0.0461 on full training set

## Call:
## rpart(formula = .outcome ~ ., control = list(minsplit = 20, minbucket = 7, 
##     cp = 0, maxcompete = 4, maxsurrogate = 5, usesurrogate = 2, 
##     surrogatestyle = 0, maxdepth = 30, xval = 0))
##   n= 20000 
## 
##           CP nsplit rel error
## 1 0.09218132      0 1.0000000
## 2 0.00000000      1 0.9078187
## 
## Variable importance
## bucket2008 
##        100 
## 
## Node number 1: 20000 observations,    complexity param=0.09218132
##   predicted class=B1  expected loss=0.3287  P(node) =1
##     class counts: 13426  3803  1789   867   115
##    probabilities: 0.671 0.190 0.089 0.043 0.006 
##   left son=2 (14896 obs) right son=3 (5104 obs)
##   Primary splits:
##       bucket2008 < 1.5 to the left,  improve=1460.066, (0 missing)
## 
## Node number 2: 14896 observations
##   predicted class=B1  expected loss=0.1942132  P(node) =0.7448
##     class counts: 12003  1774   797   289    33
##    probabilities: 0.806 0.119 0.054 0.019 0.002 
## 
## Node number 3: 5104 observations
##   predicted class=B2  expected loss=0.6024687  P(node) =0.2552
##     class counts:  1423  2029   992   578    82
##    probabilities: 0.279 0.398 0.194 0.113 0.016 
## 
## n= 20000 
## 
## node), split, n, loss, yval, (yprob)
##       * denotes terminal node
## 
## 1) root 20000 6574 B1 (0.67 0.19 0.089 0.043 0.0057)  
##   2) bucket2008< 1.5 14896 2893 B1 (0.81 0.12 0.054 0.019 0.0022) *
##   3) bucket2008>=1.5 5104 3075 B2 (0.28 0.4 0.19 0.11 0.016) *
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12003  1423     0     0     0
##        B2  1774  2029     0     0     0
##        B3   797   992     0     0     0
##        B4   289   578     0     0     0
##        B5    33    82     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.016000e-01   3.390765e-01   6.952047e-01   7.079366e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   1.965498e-20            NaN 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12059  1367     0     0     0
##        B2  1775  2029     0     0     0
##        B3   782  1007     0     0     0
##        B4   296   570     0     0     0
##        B5    34    81     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.044000e-01   3.435108e-01   6.980216e-01   7.107190e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   4.678447e-24            NaN 
##               model_id model_method      feats max.nTuningRuns
## 1 Max.cor.Y.cv.G.rpart        rpart bucket2008               3
##   min.elapsedtime.everything min.elapsedtime.final max.Accuracy.fit
## 1                      2.316                 0.246        0.7015991
##   max.AccuracyLower.fit max.AccuracyUpper.fit max.Kappa.fit
## 1             0.6952047             0.7079366     0.3390926
##   max.Accuracy.OOB max.AccuracyLower.OOB max.AccuracyUpper.OOB
## 1           0.7044             0.6980216              0.710719
##   max.Kappa.OOB min.SSE.fit max.AccuracySD.fit max.KappaSD.fit
## 1     0.3435108           0        0.004432663     0.007882575
# Interactions.High.cor.Y
if (nrow(int_feats_df <- subset(glb_feats_df, (cor.low == 0) & 
                                              (exclude.as.feat == 0))) > 0) {
    # Only glm handles interaction terms (checked that rpart does not)
    #   This does not work - why ???
#     indep_vars_vctr <- ifelse(glb_is_binomial, 
#         c(max_cor_y_x_var, paste(max_cor_y_x_var, 
#                         subset(glb_feats_df, is.na(cor.low))[, "id"], sep=":")),
#         union(max_cor_y_x_var, subset(glb_feats_df, is.na(cor.low))[, "id"]))
    if (glb_is_regression | glb_is_binomial) {
        indep_vars_vctr <- 
            c(max_cor_y_x_var, paste(max_cor_y_x_var, int_feats_df[, "id"], sep=":"))       
    } else { indep_vars_vctr <- union(max_cor_y_x_var, int_feats_df[, "id"]) }
    
    ret_lst <- myfit_mdl_fn(model_id="Interact.High.cor.y", 
                            model_method=ifelse(glb_is_regression, "lm", 
                                        ifelse(glb_is_binomial, "glm", "rpart")),
                            indep_vars_vctr,
                            glb_rsp_var, glb_rsp_var_out,
                            fit_df=glb_entity_df, OOB_df=glb_newent_df,
                            n_cv_folds=glb_n_cv_folds, tune_models_df=NULL)                        
}    
## [1] "fitting model: Interact.High.cor.y.rpart"
## [1] "    indep_vars: bucket2008, reimbursement2008"
## + Fold1: cp=0.0004563 
## - Fold1: cp=0.0004563 
## + Fold2: cp=0.0004563 
## - Fold2: cp=0.0004563 
## + Fold3: cp=0.0004563 
## - Fold3: cp=0.0004563 
## + Fold4: cp=0.0004563 
## - Fold4: cp=0.0004563 
## + Fold5: cp=0.0004563 
## - Fold5: cp=0.0004563 
## Aggregating results
## Selecting tuning parameters
## Fitting cp = 0.000487 on full training set

## Call:
## rpart(formula = .outcome ~ ., control = list(minsplit = 20, minbucket = 7, 
##     cp = 0, maxcompete = 4, maxsurrogate = 5, usesurrogate = 2, 
##     surrogatestyle = 0, maxdepth = 30, xval = 0))
##   n= 20000 
## 
##            CP nsplit rel error
## 1 0.046775175      0 1.0000000
## 2 0.000486766      2 0.9064497
## 
## Variable importance
## reimbursement2008        bucket2008 
##                60                40 
## 
## Node number 1: 20000 observations,    complexity param=0.04677517
##   predicted class=B1  expected loss=0.3287  P(node) =1
##     class counts: 13426  3803  1789   867   115
##    probabilities: 0.671 0.190 0.089 0.043 0.006 
##   left son=2 (12142 obs) right son=3 (7858 obs)
##   Primary splits:
##       reimbursement2008 < 1565 to the left,  improve=1764.349, (0 missing)
##       bucket2008        < 1.5  to the left,  improve=1460.066, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5  to the left,  agree=0.862, adj=0.65, (0 split)
## 
## Node number 2: 12142 observations
##   predicted class=B1  expected loss=0.1275737  P(node) =0.6071
##     class counts: 10593   933   433   164    19
##    probabilities: 0.872 0.077 0.036 0.014 0.002 
## 
## Node number 3: 7858 observations,    complexity param=0.04677517
##   predicted class=B2  expected loss=0.6347671  P(node) =0.3929
##     class counts:  2833  2870  1356   703    96
##    probabilities: 0.361 0.365 0.173 0.089 0.012 
##   left son=6 (3262 obs) right son=7 (4596 obs)
##   Primary splits:
##       reimbursement2008 < 3425 to the left,  improve=138.7998, (0 missing)
##       bucket2008        < 1.5  to the left,  improve=127.8257, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5  to the left,  agree=0.935, adj=0.844, (0 split)
## 
## Node number 6: 3262 observations
##   predicted class=B1  expected loss=0.5012262  P(node) =0.1631
##     class counts:  1627  1049   415   155    16
##    probabilities: 0.499 0.322 0.127 0.048 0.005 
## 
## Node number 7: 4596 observations
##   predicted class=B2  expected loss=0.6037859  P(node) =0.2298
##     class counts:  1206  1821   941   548    80
##    probabilities: 0.262 0.396 0.205 0.119 0.017 
## 
## n= 20000 
## 
## node), split, n, loss, yval, (yprob)
##       * denotes terminal node
## 
## 1) root 20000 6574 B1 (0.67 0.19 0.089 0.043 0.0057)  
##   2) reimbursement2008< 1565 12142 1549 B1 (0.87 0.077 0.036 0.014 0.0016) *
##   3) reimbursement2008>=1565 7858 4988 B2 (0.36 0.37 0.17 0.089 0.012)  
##     6) reimbursement2008< 3425 3262 1635 B1 (0.5 0.32 0.13 0.048 0.0049) *
##     7) reimbursement2008>=3425 4596 2775 B2 (0.26 0.4 0.2 0.12 0.017) *
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12220  1206     0     0     0
##        B2  1982  1821     0     0     0
##        B3   848   941     0     0     0
##        B4   319   548     0     0     0
##        B5    35    80     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.020500e-01   3.217129e-01   6.956574e-01   7.083838e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   5.406392e-21            NaN 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12274  1152     0     0     0
##        B2  1961  1843     0     0     0
##        B3   849   940     0     0     0
##        B4   327   539     0     0     0
##        B5    39    76     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.058500e-01   3.286550e-01   6.994804e-01   7.121597e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   4.639660e-26            NaN 
##                    model_id model_method                         feats
## 1 Interact.High.cor.y.rpart        rpart bucket2008, reimbursement2008
##   max.nTuningRuns min.elapsedtime.everything min.elapsedtime.final
## 1               3                      2.997                 0.361
##   max.Accuracy.fit max.AccuracyLower.fit max.AccuracyUpper.fit
## 1        0.6964492             0.6956574             0.7083838
##   max.Kappa.fit max.Accuracy.OOB max.AccuracyLower.OOB
## 1     0.3134828          0.70585             0.6994804
##   max.AccuracyUpper.OOB max.Kappa.OOB min.SSE.fit max.AccuracySD.fit
## 1             0.7121597      0.328655           0        0.004645926
##   max.KappaSD.fit
## 1      0.01363782
# Low.cor.X
ret_lst <- myfit_mdl_fn(model_id="Low.cor.X", 
                        model_method=ifelse(glb_is_regression, "lm", 
                                        ifelse(glb_is_binomial, "glm", "rpart")),
                        indep_vars_vctr=subset(glb_feats_df, cor.low == 1)[, "id"],
                        glb_rsp_var, glb_rsp_var_out,
                        fit_df=glb_entity_df, OOB_df=glb_newent_df,
                        n_cv_folds=glb_n_cv_folds, tune_models_df=NULL)
## [1] "fitting model: Low.cor.X.rpart"
## [1] "    indep_vars: bucket2008, diabetes, ihd, kidney, heart.failure, copd, depression, alzheimers, arthritis, osteoporosis, cancer, stroke, age"
## + Fold1: cp=0.003955 
## - Fold1: cp=0.003955 
## + Fold2: cp=0.003955 
## - Fold2: cp=0.003955 
## + Fold3: cp=0.003955 
## - Fold3: cp=0.003955 
## + Fold4: cp=0.003955 
## - Fold4: cp=0.003955 
## + Fold5: cp=0.003955 
## - Fold5: cp=0.003955 
## Aggregating results
## Selecting tuning parameters
## Fitting cp = 0.00395 on full training set
## Warning in myfit_mdl_fn(model_id = "Low.cor.X", model_method =
## ifelse(glb_is_regression, : model's bestTune found at an extreme of
## tuneGrid for parameter: cp

## Call:
## rpart(formula = .outcome ~ ., control = list(minsplit = 20, minbucket = 7, 
##     cp = 0, maxcompete = 4, maxsurrogate = 5, usesurrogate = 2, 
##     surrogatestyle = 0, maxdepth = 30, xval = 0))
##   n= 20000 
## 
##            CP nsplit rel error
## 1 0.092181320      0 1.0000000
## 2 0.022056587      1 0.9078187
## 3 0.003954974      2 0.8857621
## 
## Variable importance
##    bucket2008        kidney          copd heart.failure     arthritis 
##            50            15            12             9             6 
##        cancer      diabetes 
##             5             2 
## 
## Node number 1: 20000 observations,    complexity param=0.09218132
##   predicted class=B1  expected loss=0.3287  P(node) =1
##     class counts: 13426  3803  1789   867   115
##    probabilities: 0.671 0.190 0.089 0.043 0.006 
##   left son=2 (14896 obs) right son=3 (5104 obs)
##   Primary splits:
##       bucket2008    < 1.5 to the left,  improve=1460.0660, (0 missing)
##       ihd           < 0.5 to the left,  improve=1206.8110, (0 missing)
##       diabetes      < 0.5 to the left,  improve=1184.0260, (0 missing)
##       heart.failure < 0.5 to the left,  improve= 934.8263, (0 missing)
##       kidney        < 0.5 to the left,  improve= 812.4808, (0 missing)
##   Surrogate splits:
##       kidney        < 0.5 to the left,  agree=0.822, adj=0.304, (0 split)
##       copd          < 0.5 to the left,  agree=0.807, adj=0.245, (0 split)
##       heart.failure < 0.5 to the left,  agree=0.790, adj=0.178, (0 split)
##       arthritis     < 0.5 to the left,  agree=0.778, adj=0.130, (0 split)
##       cancer        < 0.5 to the left,  agree=0.773, adj=0.109, (0 split)
## 
## Node number 2: 14896 observations
##   predicted class=B1  expected loss=0.1942132  P(node) =0.7448
##     class counts: 12003  1774   797   289    33
##    probabilities: 0.806 0.119 0.054 0.019 0.002 
## 
## Node number 3: 5104 observations,    complexity param=0.02205659
##   predicted class=B2  expected loss=0.6024687  P(node) =0.2552
##     class counts:  1423  2029   992   578    82
##    probabilities: 0.279 0.398 0.194 0.113 0.016 
##   left son=6 (1173 obs) right son=7 (3931 obs)
##   Primary splits:
##       diabetes      < 0.5 to the left,  improve=61.80990, (0 missing)
##       kidney        < 0.5 to the left,  improve=49.96595, (0 missing)
##       ihd           < 0.5 to the left,  improve=37.56770, (0 missing)
##       arthritis     < 0.5 to the left,  improve=37.20455, (0 missing)
##       heart.failure < 0.5 to the left,  improve=30.56999, (0 missing)
## 
## Node number 6: 1173 observations
##   predicted class=B1  expected loss=0.544757  P(node) =0.05865
##     class counts:   534   389   181    65     4
##    probabilities: 0.455 0.332 0.154 0.055 0.003 
## 
## Node number 7: 3931 observations
##   predicted class=B2  expected loss=0.5828034  P(node) =0.19655
##     class counts:   889  1640   811   513    78
##    probabilities: 0.226 0.417 0.206 0.131 0.020 
## 
## n= 20000 
## 
## node), split, n, loss, yval, (yprob)
##       * denotes terminal node
## 
## 1) root 20000 6574 B1 (0.67 0.19 0.089 0.043 0.0057)  
##   2) bucket2008< 1.5 14896 2893 B1 (0.81 0.12 0.054 0.019 0.0022) *
##   3) bucket2008>=1.5 5104 3075 B2 (0.28 0.4 0.19 0.11 0.016)  
##     6) diabetes< 0.5 1173  639 B1 (0.46 0.33 0.15 0.055 0.0034) *
##     7) diabetes>=0.5 3931 2291 B2 (0.23 0.42 0.21 0.13 0.02) *
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12537   889     0     0     0
##        B2  2163  1640     0     0     0
##        B3   978   811     0     0     0
##        B4   354   513     0     0     0
##        B5    37    78     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.088500e-01   3.121412e-01   7.024989e-01   7.151403e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   1.753084e-30            NaN 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12531   895     0     0     0
##        B2  2199  1605     0     0     0
##        B3   947   842     0     0     0
##        B4   364   502     0     0     0
##        B5    37    78     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.068000e-01   3.069274e-01   7.004362e-01   7.131036e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   2.025337e-27            NaN 
##          model_id model_method
## 1 Low.cor.X.rpart        rpart
##                                                                                                                          feats
## 1 bucket2008, diabetes, ihd, kidney, heart.failure, copd, depression, alzheimers, arthritis, osteoporosis, cancer, stroke, age
##   max.nTuningRuns min.elapsedtime.everything min.elapsedtime.final
## 1               3                      6.536                 0.866
##   max.Accuracy.fit max.AccuracyLower.fit max.AccuracyUpper.fit
## 1        0.7092992             0.7024989             0.7151403
##   max.Kappa.fit max.Accuracy.OOB max.AccuracyLower.OOB
## 1     0.3218867           0.7068             0.7004362
##   max.AccuracyUpper.OOB max.Kappa.OOB min.SSE.fit max.AccuracySD.fit
## 1             0.7131036     0.3069274           0        0.005333283
##   max.KappaSD.fit
## 1      0.01238742
# User specified
for (method in glb_models_method_vctr) {
    print(sprintf("iterating over method:%s", method))

    # All X that is not user excluded
    indep_vars_vctr <- setdiff(names(glb_entity_df), 
        union(glb_rsp_var, glb_exclude_vars_as_features))
    
    # easier to exclude features
#     indep_vars_vctr <- setdiff(names(glb_entity_df), 
#         union(union(glb_rsp_var, glb_exclude_vars_as_features), 
#               c("<feat1_name>", "<feat2_name>")))
    
    # easier to include features
#     indep_vars_vctr <- c("<feat1_name>", "<feat2_name>")

    # User specified bivariate models
#     indep_vars_vctr_lst <- list()
#     for (feat in setdiff(names(glb_entity_df), 
#                          union(glb_rsp_var, glb_exclude_vars_as_features)))
#         indep_vars_vctr_lst[["feat"]] <- feat

    # User specified combinatorial models
#     indep_vars_vctr_lst <- list()
#     combn_mtrx <- combn(c("<feat1_name>", "<feat2_name>", "<featn_name>"), 
#                           <num_feats_to_choose>)
#     for (combn_ix in 1:ncol(combn_mtrx))
#         #print(combn_mtrx[, combn_ix])
#         indep_vars_vctr_lst[[combn_ix]] <- combn_mtrx[, combn_ix]

#     glb_sel_mdl <- glb_sel_wlm_mdl <- ret_lst[["model"]]
#     rpart_sel_wlm_mdl <- rpart(reformulate(indep_vars_vctr, response=glb_rsp_var), 
#                                data=glb_entity_df, method="class", 
#                                control=rpart.control(cp=glb_sel_wlm_mdl$bestTune$cp),
#                            parms=list(loss=glb_model_metric_terms))
#     print("rpart_sel_wlm_mdl"); prp(rpart_sel_wlm_mdl)
# 
    model_id_pfx <- "All.X";
    ret_lst <- myfit_mdl_fn(model_id=paste0(model_id_pfx, ".lser.no.cp.opt"), model_method=method,
                            indep_vars_vctr=indep_vars_vctr,
                            rsp_var=glb_rsp_var, rsp_var_out=glb_rsp_var_out,
                            fit_df=glb_entity_df, OOB_df=glb_newent_df,
                            n_cv_folds=glb_n_cv_folds, tune_models_df=NULL)
    ret_lst <- myfit_mdl_fn(model_id=paste0(model_id_pfx, ".lser.no.cp.4015"), model_method=method,
                            indep_vars_vctr=indep_vars_vctr,
                            rsp_var=glb_rsp_var, rsp_var_out=glb_rsp_var_out,
                            fit_df=glb_entity_df, OOB_df=glb_newent_df,
                            n_cv_folds=glb_n_cv_folds, tune_models_df=glb_tune_models_df)
    ret_lst <- myfit_mdl_fn(model_id=paste0(model_id_pfx, ".lser.ys.cp.opt"), model_method=method,
                            indep_vars_vctr=indep_vars_vctr,
                            rsp_var=glb_rsp_var, rsp_var_out=glb_rsp_var_out,
                            fit_df=glb_entity_df, OOB_df=glb_newent_df,
                            n_cv_folds=glb_n_cv_folds, tune_models_df=NULL,
                            model_loss_mtrx=glb_model_metric_terms,
                            model_summaryFunction=glb_model_metric_smmry,
                            model_metric=glb_model_metric,
                            model_metric_maximize=glb_model_metric_maximize)
    ret_lst <- myfit_mdl_fn(model_id=paste0(model_id_pfx, ".lser.ys.cp.4015"), model_method=method,
                            indep_vars_vctr=indep_vars_vctr,
                            rsp_var=glb_rsp_var, rsp_var_out=glb_rsp_var_out,
                            fit_df=glb_entity_df, OOB_df=glb_newent_df,
                            n_cv_folds=glb_n_cv_folds, tune_models_df=glb_tune_models_df,
                            model_loss_mtrx=glb_model_metric_terms,
                            model_summaryFunction=glb_model_metric_smmry,
                            model_metric=glb_model_metric,
                            model_metric_maximize=glb_model_metric_maximize)
}
## [1] "iterating over method:rpart"
## [1] "fitting model: All.X.lser.no.cp.opt.rpart"
## [1] "    indep_vars: age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008"
## + Fold1: cp=0.00502 
## - Fold1: cp=0.00502 
## + Fold2: cp=0.00502 
## - Fold2: cp=0.00502 
## + Fold3: cp=0.00502 
## - Fold3: cp=0.00502 
## + Fold4: cp=0.00502 
## - Fold4: cp=0.00502 
## + Fold5: cp=0.00502 
## - Fold5: cp=0.00502 
## Aggregating results
## Selecting tuning parameters
## Fitting cp = 0.00502 on full training set
## Warning in myfit_mdl_fn(model_id = paste0(model_id_pfx,
## ".lser.no.cp.opt"), : model's bestTune found at an extreme of tuneGrid for
## parameter: cp

## Call:
## rpart(formula = .outcome ~ ., control = list(minsplit = 20, minbucket = 7, 
##     cp = 0, maxcompete = 4, maxsurrogate = 5, usesurrogate = 2, 
##     surrogatestyle = 0, maxdepth = 30, xval = 0))
##   n= 20000 
## 
##            CP nsplit rel error
## 1 0.046775175      0 1.0000000
## 2 0.017036812      2 0.9064497
## 3 0.005019775      3 0.8894128
## 
## Variable importance
## reimbursement2008        bucket2008          diabetes               ihd 
##                31                21                14                14 
##     heart.failure            kidney 
##                12                 9 
## 
## Node number 1: 20000 observations,    complexity param=0.04677517
##   predicted class=B1  expected loss=0.3287  P(node) =1
##     class counts: 13426  3803  1789   867   115
##    probabilities: 0.671 0.190 0.089 0.043 0.006 
##   left son=2 (12142 obs) right son=3 (7858 obs)
##   Primary splits:
##       reimbursement2008 < 1565  to the left,  improve=1764.3490, (0 missing)
##       bucket2008        < 1.5   to the left,  improve=1460.0660, (0 missing)
##       ihd               < 0.5   to the left,  improve=1206.8110, (0 missing)
##       diabetes          < 0.5   to the left,  improve=1184.0260, (0 missing)
##       heart.failure     < 0.5   to the left,  improve= 934.8263, (0 missing)
##   Surrogate splits:
##       bucket2008    < 1.5   to the left,  agree=0.862, adj=0.650, (0 split)
##       ihd           < 0.5   to the left,  agree=0.790, adj=0.466, (0 split)
##       diabetes      < 0.5   to the left,  agree=0.784, adj=0.449, (0 split)
##       heart.failure < 0.5   to the left,  agree=0.763, adj=0.397, (0 split)
##       kidney        < 0.5   to the left,  agree=0.732, adj=0.319, (0 split)
## 
## Node number 2: 12142 observations
##   predicted class=B1  expected loss=0.1275737  P(node) =0.6071
##     class counts: 10593   933   433   164    19
##    probabilities: 0.872 0.077 0.036 0.014 0.002 
## 
## Node number 3: 7858 observations,    complexity param=0.04677517
##   predicted class=B2  expected loss=0.6347671  P(node) =0.3929
##     class counts:  2833  2870  1356   703    96
##    probabilities: 0.361 0.365 0.173 0.089 0.012 
##   left son=6 (3262 obs) right son=7 (4596 obs)
##   Primary splits:
##       reimbursement2008 < 3425  to the left,  improve=138.79980, (0 missing)
##       bucket2008        < 1.5   to the left,  improve=127.82570, (0 missing)
##       kidney            < 0.5   to the left,  improve=108.01160, (0 missing)
##       diabetes          < 0.5   to the left,  improve= 91.30944, (0 missing)
##       ihd               < 0.5   to the left,  improve= 83.33736, (0 missing)
##   Surrogate splits:
##       bucket2008    < 1.5   to the left,  agree=0.935, adj=0.844, (0 split)
##       heart.failure < 0.5   to the left,  agree=0.636, adj=0.122, (0 split)
##       kidney        < 0.5   to the left,  agree=0.634, adj=0.117, (0 split)
##       ihd           < 0.5   to the left,  agree=0.631, adj=0.111, (0 split)
##       diabetes      < 0.5   to the left,  agree=0.623, adj=0.092, (0 split)
## 
## Node number 6: 3262 observations
##   predicted class=B1  expected loss=0.5012262  P(node) =0.1631
##     class counts:  1627  1049   415   155    16
##    probabilities: 0.499 0.322 0.127 0.048 0.005 
## 
## Node number 7: 4596 observations,    complexity param=0.01703681
##   predicted class=B2  expected loss=0.6037859  P(node) =0.2298
##     class counts:  1206  1821   941   548    80
##    probabilities: 0.262 0.396 0.205 0.119 0.017 
##   left son=14 (1002 obs) right son=15 (3594 obs)
##   Primary splits:
##       diabetes          < 0.5   to the left,  improve=54.64315, (0 missing)
##       kidney            < 0.5   to the left,  improve=39.83945, (0 missing)
##       arthritis         < 0.5   to the left,  improve=27.98163, (0 missing)
##       ihd               < 0.5   to the left,  improve=27.96369, (0 missing)
##       reimbursement2008 < 14985 to the left,  improve=24.59678, (0 missing)
## 
## Node number 14: 1002 observations
##   predicted class=B1  expected loss=0.5568862  P(node) =0.0501
##     class counts:   444   332   169    54     3
##    probabilities: 0.443 0.331 0.169 0.054 0.003 
## 
## Node number 15: 3594 observations
##   predicted class=B2  expected loss=0.5856984  P(node) =0.1797
##     class counts:   762  1489   772   494    77
##    probabilities: 0.212 0.414 0.215 0.137 0.021 
## 
## n= 20000 
## 
## node), split, n, loss, yval, (yprob)
##       * denotes terminal node
## 
##  1) root 20000 6574 B1 (0.67 0.19 0.089 0.043 0.0057)  
##    2) reimbursement2008< 1565 12142 1549 B1 (0.87 0.077 0.036 0.014 0.0016) *
##    3) reimbursement2008>=1565 7858 4988 B2 (0.36 0.37 0.17 0.089 0.012)  
##      6) reimbursement2008< 3425 3262 1635 B1 (0.5 0.32 0.13 0.048 0.0049) *
##      7) reimbursement2008>=3425 4596 2775 B2 (0.26 0.4 0.2 0.12 0.017)  
##       14) diabetes< 0.5 1002  558 B1 (0.44 0.33 0.17 0.054 0.003) *
##       15) diabetes>=0.5 3594 2105 B2 (0.21 0.41 0.21 0.14 0.021) *
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12664   762     0     0     0
##        B2  2314  1489     0     0     0
##        B3  1017   772     0     0     0
##        B4   373   494     0     0     0
##        B5    38    77     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.076500e-01   2.958182e-01   7.012915e-01   7.139481e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   1.142501e-28            NaN 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12662   764     0     0     0
##        B2  2322  1482     0     0     0
##        B3   999   790     0     0     0
##        B4   392   474     0     0     0
##        B5    42    73     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.072000e-01   2.942692e-01   7.008387e-01   7.135010e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   5.280171e-28            NaN 
##                     model_id model_method
## 1 All.X.lser.no.cp.opt.rpart        rpart
##                                                                                                                                             feats
## 1 age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
##   max.nTuningRuns min.elapsedtime.everything min.elapsedtime.final
## 1               3                      6.806                 0.919
##   max.Accuracy.fit max.AccuracyLower.fit max.AccuracyUpper.fit
## 1        0.7074489             0.7012915             0.7139481
##   max.Kappa.fit max.Accuracy.OOB max.AccuracyLower.OOB
## 1     0.3038255           0.7072             0.7008387
##   max.AccuracyUpper.OOB max.Kappa.OOB min.SSE.fit max.AccuracySD.fit
## 1              0.713501     0.2942692           0        0.006818137
##   max.KappaSD.fit
## 1      0.02061198
## [1] "fitting model: All.X.lser.no.cp.4015.rpart"
## [1] "    indep_vars: age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008"
## + Fold1: cp=5e-05 
## - Fold1: cp=5e-05 
## + Fold2: cp=5e-05 
## - Fold2: cp=5e-05 
## + Fold3: cp=5e-05 
## - Fold3: cp=5e-05 
## + Fold4: cp=5e-05 
## - Fold4: cp=5e-05 
## + Fold5: cp=5e-05 
## - Fold5: cp=5e-05 
## Aggregating results
## Fitting final model on full training set
## Warning: labs do not fit even at cex 0.15, there may be some overplotting

## Call:
## rpart(formula = .outcome ~ ., control = list(minsplit = 20, minbucket = 7, 
##     cp = 0, maxcompete = 4, maxsurrogate = 5, usesurrogate = 2, 
##     surrogatestyle = 0, maxdepth = 30, xval = 0))
##   n= 20000 
## 
##              CP nsplit rel error
## 1  4.677517e-02      0 1.0000000
## 2  1.703681e-02      2 0.9064497
## 3  5.019775e-03      3 0.8894128
## 4  3.346517e-03      4 0.8843931
## 5  2.053544e-03      7 0.8743535
## 6  1.216915e-03      9 0.8702464
## 7  1.064801e-03     11 0.8678126
## 8  9.126863e-04     16 0.8624886
## 9  8.746577e-04     17 0.8615759
## 10 8.619815e-04     26 0.8522969
## 11 7.605720e-04     29 0.8497110
## 12 6.084576e-04     34 0.8459081
## 13 5.324004e-04     44 0.8398235
## 14 5.070480e-04     50 0.8366291
## 15 4.563432e-04     83 0.8183754
## 16 4.056384e-04    110 0.8060542
## 17 3.802860e-04    115 0.8039246
## 18 3.650745e-04    134 0.7966231
## 19 3.549336e-04    144 0.7928202
## 20 3.422574e-04    164 0.7852145
## 21 3.295812e-04    168 0.7838455
## 22 3.042288e-04    174 0.7818680
## 23 2.788764e-04    222 0.7671129
## 24 2.738059e-04    230 0.7648312
## 25 2.662002e-04    238 0.7620931
## 26 2.535240e-04    246 0.7599635
## 27 2.281716e-04    262 0.7555522
## 28 2.028192e-04    301 0.7449042
## 29 1.901430e-04    329 0.7380590
## 30 1.521144e-04    345 0.7345604
## 31 1.303838e-04    438 0.7191968
## 32 1.216915e-04    445 0.7182841
## 33 1.014096e-04    459 0.7161545
## 34 8.450799e-05    475 0.7143292
## 35 7.605720e-05    485 0.7134165
## 36 6.519188e-05    527 0.7102221
## 37 6.084576e-05    560 0.7079404
## 38 5.070480e-05    567 0.7074840
## 39 5.000000e-05    573 0.7071798
## 
## Variable importance
## reimbursement2008        bucket2008          diabetes               ihd 
##                32                17                12                12 
##     heart.failure            kidney               age        depression 
##                10                 8                 4                 1 
##      osteoporosis              copd         arthritis        alzheimers 
##                 1                 1                 1                 1 
## 
## Node number 1: 20000 observations,    complexity param=0.04677517
##   predicted class=B1  expected loss=0.3287  P(node) =1
##     class counts: 13426  3803  1789   867   115
##    probabilities: 0.671 0.190 0.089 0.043 0.006 
##   left son=2 (12142 obs) right son=3 (7858 obs)
##   Primary splits:
##       reimbursement2008 < 1565   to the left,  improve=1764.3490, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=1460.0660, (0 missing)
##       ihd               < 0.5    to the left,  improve=1206.8110, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1184.0260, (0 missing)
##       heart.failure     < 0.5    to the left,  improve= 934.8263, (0 missing)
##   Surrogate splits:
##       bucket2008    < 1.5    to the left,  agree=0.862, adj=0.650, (0 split)
##       ihd           < 0.5    to the left,  agree=0.790, adj=0.466, (0 split)
##       diabetes      < 0.5    to the left,  agree=0.784, adj=0.449, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.763, adj=0.397, (0 split)
##       kidney        < 0.5    to the left,  agree=0.732, adj=0.319, (0 split)
## 
## Node number 2: 12142 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.1275737  P(node) =0.6071
##     class counts: 10593   933   433   164    19
##    probabilities: 0.872 0.077 0.036 0.014 0.002 
##   left son=4 (6456 obs) right son=5 (5686 obs)
##   Primary splits:
##       reimbursement2008 < 195    to the left,  improve=186.28990, (0 missing)
##       diabetes          < 0.5    to the left,  improve=101.76450, (0 missing)
##       ihd               < 0.5    to the left,  improve= 95.31422, (0 missing)
##       heart.failure     < 0.5    to the left,  improve= 56.11198, (0 missing)
##       depression        < 0.5    to the left,  improve= 42.49380, (0 missing)
##   Surrogate splits:
##       ihd           < 0.5    to the left,  agree=0.707, adj=0.374, (0 split)
##       diabetes      < 0.5    to the left,  agree=0.692, adj=0.343, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.630, adj=0.209, (0 split)
##       depression    < 0.5    to the left,  agree=0.608, adj=0.163, (0 split)
##       osteoporosis  < 0.5    to the left,  agree=0.606, adj=0.158, (0 split)
## 
## Node number 3: 7858 observations,    complexity param=0.04677517
##   predicted class=B2  expected loss=0.6347671  P(node) =0.3929
##     class counts:  2833  2870  1356   703    96
##    probabilities: 0.361 0.365 0.173 0.089 0.012 
##   left son=6 (3262 obs) right son=7 (4596 obs)
##   Primary splits:
##       reimbursement2008 < 3425   to the left,  improve=138.79980, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=127.82570, (0 missing)
##       kidney            < 0.5    to the left,  improve=108.01160, (0 missing)
##       diabetes          < 0.5    to the left,  improve= 91.30944, (0 missing)
##       ihd               < 0.5    to the left,  improve= 83.33736, (0 missing)
##   Surrogate splits:
##       bucket2008    < 1.5    to the left,  agree=0.935, adj=0.844, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.636, adj=0.122, (0 split)
##       kidney        < 0.5    to the left,  agree=0.634, adj=0.117, (0 split)
##       ihd           < 0.5    to the left,  agree=0.631, adj=0.111, (0 split)
##       diabetes      < 0.5    to the left,  agree=0.623, adj=0.092, (0 split)
## 
## Node number 4: 6456 observations
##   predicted class=B1  expected loss=0.03175341  P(node) =0.3228
##     class counts:  6251   108    69    25     3
##    probabilities: 0.968 0.017 0.011 0.004 0.000 
## 
## Node number 5: 5686 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.23637  P(node) =0.2843
##     class counts:  4342   825   364   139    16
##    probabilities: 0.764 0.145 0.064 0.024 0.003 
##   left son=10 (2374 obs) right son=11 (3312 obs)
##   Primary splits:
##       reimbursement2008 < 685    to the left,  improve=27.349520, (0 missing)
##       diabetes          < 0.5    to the left,  improve=17.262440, (0 missing)
##       ihd               < 0.5    to the left,  improve=13.874990, (0 missing)
##       heart.failure     < 0.5    to the left,  improve= 8.237337, (0 missing)
##       depression        < 0.5    to the left,  improve= 7.708074, (0 missing)
##   Surrogate splits:
##       diabetes < 0.5    to the left,  agree=0.586, adj=0.008, (0 split)
## 
## Node number 6: 3262 observations,    complexity param=0.003346517
##   predicted class=B1  expected loss=0.5012262  P(node) =0.1631
##     class counts:  1627  1049   415   155    16
##    probabilities: 0.499 0.322 0.127 0.048 0.005 
##   left son=12 (1087 obs) right son=13 (2175 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=22.12235, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=18.39133, (0 missing)
##       kidney            < 0.5    to the left,  improve=16.45818, (0 missing)
##       reimbursement2008 < 2535   to the left,  improve=15.04368, (0 missing)
##       arthritis         < 0.5    to the left,  improve=14.50169, (0 missing)
## 
## Node number 7: 4596 observations,    complexity param=0.01703681
##   predicted class=B2  expected loss=0.6037859  P(node) =0.2298
##     class counts:  1206  1821   941   548    80
##    probabilities: 0.262 0.396 0.205 0.119 0.017 
##   left son=14 (1002 obs) right son=15 (3594 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=54.64315, (0 missing)
##       kidney            < 0.5    to the left,  improve=39.83945, (0 missing)
##       arthritis         < 0.5    to the left,  improve=27.98163, (0 missing)
##       ihd               < 0.5    to the left,  improve=27.96369, (0 missing)
##       reimbursement2008 < 14985  to the left,  improve=24.59678, (0 missing)
## 
## Node number 10: 2374 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1693345  P(node) =0.1187
##     class counts:  1972   239   123    35     5
##    probabilities: 0.831 0.101 0.052 0.015 0.002 
##   left son=20 (1860 obs) right son=21 (514 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=2.303753, (0 missing)
##       reimbursement2008 < 415    to the left,  improve=1.555073, (0 missing)
##       age               < 89.5   to the left,  improve=1.295020, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.286801, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.280980, (0 missing)
## 
## Node number 11: 3312 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.2844203  P(node) =0.1656
##     class counts:  2370   586   241   104    11
##    probabilities: 0.716 0.177 0.073 0.031 0.003 
##   left son=22 (1722 obs) right son=23 (1590 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=7.957796, (0 missing)
##       diabetes          < 0.5    to the left,  improve=6.966093, (0 missing)
##       reimbursement2008 < 1185   to the left,  improve=5.843071, (0 missing)
##       kidney            < 0.5    to the left,  improve=4.261749, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=4.259057, (0 missing)
##   Surrogate splits:
##       heart.failure     < 0.5    to the left,  agree=0.581, adj=0.127, (0 split)
##       diabetes          < 0.5    to the left,  agree=0.570, adj=0.104, (0 split)
##       reimbursement2008 < 1285   to the left,  agree=0.551, adj=0.065, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.542, adj=0.045, (0 split)
##       kidney            < 0.5    to the left,  agree=0.542, adj=0.045, (0 split)
## 
## Node number 12: 1087 observations,    complexity param=0.000760572
##   predicted class=B1  expected loss=0.4066237  P(node) =0.05435
##     class counts:   645   279   123    36     4
##    probabilities: 0.593 0.257 0.113 0.033 0.004 
##   left son=24 (941 obs) right son=25 (146 obs)
##   Primary splits:
##       kidney        < 0.5    to the left,  improve=6.950529, (0 missing)
##       heart.failure < 0.5    to the left,  improve=5.539453, (0 missing)
##       copd          < 0.5    to the left,  improve=3.363659, (0 missing)
##       diabetes      < 0.5    to the left,  improve=3.245895, (0 missing)
##       osteoporosis  < 0.5    to the left,  improve=2.285942, (0 missing)
## 
## Node number 13: 2175 observations,    complexity param=0.003346517
##   predicted class=B1  expected loss=0.5485057  P(node) =0.10875
##     class counts:   982   770   292   119    12
##    probabilities: 0.451 0.354 0.134 0.055 0.006 
##   left son=26 (1275 obs) right son=27 (900 obs)
##   Primary splits:
##       reimbursement2008 < 2515   to the left,  improve=11.475830, (0 missing)
##       arthritis         < 0.5    to the left,  improve=10.277840, (0 missing)
##       heart.failure     < 0.5    to the left,  improve= 7.801216, (0 missing)
##       kidney            < 0.5    to the left,  improve= 7.393483, (0 missing)
##       bucket2008        < 1.5    to the left,  improve= 6.716155, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.762, adj=0.426, (0 split)
##       copd       < 0.5    to the left,  agree=0.592, adj=0.013, (0 split)
##       age        < 33     to the right, agree=0.590, adj=0.010, (0 split)
## 
## Node number 14: 1002 observations,    complexity param=0.005019775
##   predicted class=B1  expected loss=0.5568862  P(node) =0.0501
##     class counts:   444   332   169    54     3
##    probabilities: 0.443 0.331 0.169 0.054 0.003 
##   left son=28 (682 obs) right son=29 (320 obs)
##   Primary splits:
##       depression   < 0.5    to the left,  improve=13.412950, (0 missing)
##       cancer       < 0.5    to the left,  improve= 8.676806, (0 missing)
##       osteoporosis < 0.5    to the left,  improve= 6.334493, (0 missing)
##       arthritis    < 0.5    to the left,  improve= 6.023249, (0 missing)
##       ihd          < 0.5    to the left,  improve= 5.212491, (0 missing)
##   Surrogate splits:
##       age < 49.5   to the right, agree=0.682, adj=0.003, (0 split)
## 
## Node number 15: 3594 observations,    complexity param=0.0008746577
##   predicted class=B2  expected loss=0.5856984  P(node) =0.1797
##     class counts:   762  1489   772   494    77
##    probabilities: 0.212 0.414 0.215 0.137 0.021 
##   left son=30 (1568 obs) right son=31 (2026 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=29.54937, (0 missing)
##       reimbursement2008 < 14405  to the left,  improve=18.69161, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=16.83945, (0 missing)
##       arthritis         < 0.5    to the left,  improve=15.87697, (0 missing)
##       ihd               < 0.5    to the left,  improve=11.13037, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 7325   to the left,  agree=0.660, adj=0.220, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.658, adj=0.217, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.633, adj=0.159, (0 split)
##       ihd               < 0.5    to the left,  agree=0.598, adj=0.078, (0 split)
##       copd              < 0.5    to the left,  agree=0.593, adj=0.067, (0 split)
## 
## Node number 20: 1860 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1553763  P(node) =0.093
##     class counts:  1571   176    86    23     4
##    probabilities: 0.845 0.095 0.046 0.012 0.002 
##   left son=40 (1774 obs) right son=41 (86 obs)
##   Primary splits:
##       age               < 89.5   to the left,  improve=1.8556120, (0 missing)
##       reimbursement2008 < 665    to the left,  improve=0.6577829, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.6342891, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5532770, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5456541, (0 missing)
## 
## Node number 21: 514 observations,    complexity param=5.07048e-05
##   predicted class=B1  expected loss=0.2198444  P(node) =0.0257
##     class counts:   401    63    37    12     1
##    probabilities: 0.780 0.123 0.072 0.023 0.002 
##   left son=42 (173 obs) right son=43 (341 obs)
##   Primary splits:
##       reimbursement2008 < 425    to the left,  improve=1.4829330, (0 missing)
##       age               < 94.5   to the right, improve=0.8488381, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5210342, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.4383554, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.3942705, (0 missing)
##   Surrogate splits:
##       age < 98.5   to the right, agree=0.671, adj=0.023, (0 split)
## 
## Node number 22: 1722 observations,    complexity param=0.0001303838
##   predicted class=B1  expected loss=0.2462253  P(node) =0.0861
##     class counts:  1298   261   107    51     5
##    probabilities: 0.754 0.152 0.062 0.030 0.003 
##   left son=44 (951 obs) right son=45 (771 obs)
##   Primary splits:
##       reimbursement2008 < 1085   to the left,  improve=2.133022, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.851709, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.814680, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.791298, (0 missing)
##       depression        < 0.5    to the left,  improve=1.477471, (0 missing)
##   Surrogate splits:
##       kidney       < 0.5    to the left,  agree=0.569, adj=0.038, (0 split)
##       osteoporosis < 0.5    to the left,  agree=0.562, adj=0.022, (0 split)
##       arthritis    < 0.5    to the left,  agree=0.560, adj=0.017, (0 split)
##       diabetes     < 0.5    to the left,  agree=0.560, adj=0.017, (0 split)
##       depression   < 0.5    to the left,  agree=0.559, adj=0.016, (0 split)
## 
## Node number 23: 1590 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.3257862  P(node) =0.0795
##     class counts:  1072   325   134    53     6
##    probabilities: 0.674 0.204 0.084 0.033 0.004 
##   left son=46 (771 obs) right son=47 (819 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=3.574744, (0 missing)
##       reimbursement2008 < 1285   to the left,  improve=3.467285, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=2.297182, (0 missing)
##       age               < 27.5   to the right, improve=1.741472, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.681255, (0 missing)
##   Surrogate splits:
##       heart.failure     < 0.5    to the left,  agree=0.550, adj=0.073, (0 split)
##       reimbursement2008 < 1145   to the left,  agree=0.545, adj=0.061, (0 split)
##       kidney            < 0.5    to the left,  agree=0.535, adj=0.040, (0 split)
##       age               < 76.5   to the left,  agree=0.528, adj=0.026, (0 split)
##       depression        < 0.5    to the left,  agree=0.522, adj=0.014, (0 split)
## 
## Node number 24: 941 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.3804463  P(node) =0.04705
##     class counts:   583   229    96    29     4
##    probabilities: 0.620 0.243 0.102 0.031 0.004 
##   left son=48 (680 obs) right son=49 (261 obs)
##   Primary splits:
##       heart.failure < 0.5    to the left,  improve=4.641423, (0 missing)
##       diabetes      < 0.5    to the left,  improve=2.866491, (0 missing)
##       osteoporosis  < 0.5    to the left,  improve=1.985004, (0 missing)
##       copd          < 0.5    to the left,  improve=1.760285, (0 missing)
##       age           < 52.5   to the left,  improve=1.424379, (0 missing)
## 
## Node number 25: 146 observations,    complexity param=0.000760572
##   predicted class=B1  expected loss=0.5753425  P(node) =0.0073
##     class counts:    62    50    27     7     0
##    probabilities: 0.425 0.342 0.185 0.048 0.000 
##   left son=50 (82 obs) right son=51 (64 obs)
##   Primary splits:
##       age               < 74.5   to the left,  improve=3.6513430, (0 missing)
##       reimbursement2008 < 3080   to the right, improve=2.1345630, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.2427630, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.0530420, (0 missing)
##       copd              < 0.5    to the left,  improve=0.9560376, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1765   to the right, agree=0.575, adj=0.031, (0 split)
## 
## Node number 26: 1275 observations,    complexity param=0.001064801
##   predicted class=B1  expected loss=0.4996078  P(node) =0.06375
##     class counts:   638   409   152    68     8
##    probabilities: 0.500 0.321 0.119 0.053 0.006 
##   left son=52 (880 obs) right son=53 (395 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=5.193576, (0 missing)
##       reimbursement2008 < 1765   to the left,  improve=4.667403, (0 missing)
##       age               < 80.5   to the right, improve=3.217982, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=2.254540, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.756421, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2495   to the left,  agree=0.693, adj=0.008, (0 split)
## 
## Node number 27: 900 observations,    complexity param=0.003346517
##   predicted class=B2  expected loss=0.5988889  P(node) =0.045
##     class counts:   344   361   140    51     4
##    probabilities: 0.382 0.401 0.156 0.057 0.004 
##   left son=54 (614 obs) right son=55 (286 obs)
##   Primary splits:
##       arthritis     < 0.5    to the left,  improve=9.449426, (0 missing)
##       heart.failure < 0.5    to the left,  improve=7.177110, (0 missing)
##       kidney        < 0.5    to the left,  improve=4.982522, (0 missing)
##       copd          < 0.5    to the left,  improve=3.774501, (0 missing)
##       cancer        < 0.5    to the left,  improve=3.018782, (0 missing)
##   Surrogate splits:
##       age < 37.5   to the right, agree=0.687, adj=0.014, (0 split)
## 
## Node number 28: 682 observations,    complexity param=0.001216915
##   predicted class=B1  expected loss=0.4912023  P(node) =0.0341
##     class counts:   347   202    97    33     3
##    probabilities: 0.509 0.296 0.142 0.048 0.004 
##   left son=56 (563 obs) right son=57 (119 obs)
##   Primary splits:
##       cancer            < 0.5    to the left,  improve=8.288699, (0 missing)
##       arthritis         < 0.5    to the left,  improve=4.176438, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=3.934963, (0 missing)
##       ihd               < 0.5    to the left,  improve=3.166893, (0 missing)
##       reimbursement2008 < 8450   to the right, improve=2.733079, (0 missing)
## 
## Node number 29: 320 observations,    complexity param=0.0008619815
##   predicted class=B2  expected loss=0.59375  P(node) =0.016
##     class counts:    97   130    72    21     0
##    probabilities: 0.303 0.406 0.225 0.066 0.000 
##   left son=58 (213 obs) right son=59 (107 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.166497, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.990034, (0 missing)
##       age               < 91.5   to the right, improve=1.926250, (0 missing)
##       reimbursement2008 < 3710   to the left,  improve=1.809690, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.730409, (0 missing)
##   Surrogate splits:
##       stroke            < 0.5    to the left,  agree=0.678, adj=0.037, (0 split)
##       reimbursement2008 < 40240  to the left,  agree=0.675, adj=0.028, (0 split)
##       age               < 42.5   to the right, agree=0.672, adj=0.019, (0 split)
##       bucket2008        < 4.5    to the left,  agree=0.669, adj=0.009, (0 split)
## 
## Node number 30: 1568 observations,    complexity param=0.0008746577
##   predicted class=B2  expected loss=0.5612245  P(node) =0.0784
##     class counts:   448   688   304   117    11
##    probabilities: 0.286 0.439 0.194 0.075 0.007 
##   left son=60 (964 obs) right son=61 (604 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=9.229921, (0 missing)
##       cancer            < 0.5    to the left,  improve=6.469383, (0 missing)
##       reimbursement2008 < 59995  to the left,  improve=4.836546, (0 missing)
##       bucket2008        < 4.5    to the left,  improve=3.876636, (0 missing)
##       age               < 71.5   to the right, improve=3.803969, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 35170  to the left,  agree=0.620, adj=0.013, (0 split)
##       bucket2008        < 4.5    to the left,  agree=0.615, adj=0.002, (0 split)
## 
## Node number 31: 2026 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6046397  P(node) =0.1013
##     class counts:   314   801   468   377    66
##    probabilities: 0.155 0.395 0.231 0.186 0.033 
##   left son=62 (1090 obs) right son=63 (936 obs)
##   Primary splits:
##       reimbursement2008 < 15095  to the left,  improve=9.838861, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=7.625303, (0 missing)
##       arthritis         < 0.5    to the left,  improve=7.497489, (0 missing)
##       ihd               < 0.5    to the left,  improve=4.354999, (0 missing)
##       age               < 44.5   to the right, improve=4.056220, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the left,  agree=0.913, adj=0.811, (0 split)
##       copd       < 0.5    to the left,  agree=0.610, adj=0.156, (0 split)
##       stroke     < 0.5    to the left,  agree=0.582, adj=0.096, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.567, adj=0.063, (0 split)
##       cancer     < 0.5    to the left,  agree=0.566, adj=0.061, (0 split)
## 
## Node number 40: 1774 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1499436  P(node) =0.0887
##     class counts:  1508   165    75    23     3
##    probabilities: 0.850 0.093 0.042 0.013 0.002 
##   left son=80 (1764 obs) right son=81 (10 obs)
##   Primary splits:
##       age               < 29.5   to the right, improve=1.1538870, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8525277, (0 missing)
##       reimbursement2008 < 665    to the left,  improve=0.6307025, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5616328, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5123385, (0 missing)
## 
## Node number 41: 86 observations
##   predicted class=B1  expected loss=0.2674419  P(node) =0.0043
##     class counts:    63    11    11     0     1
##    probabilities: 0.733 0.128 0.128 0.000 0.012 
## 
## Node number 42: 173 observations,    complexity param=5.07048e-05
##   predicted class=B1  expected loss=0.1618497  P(node) =0.00865
##     class counts:   145    13    11     4     0
##    probabilities: 0.838 0.075 0.064 0.023 0.000 
##   left son=84 (147 obs) right son=85 (26 obs)
##   Primary splits:
##       age               < 64.5   to the right, improve=2.0458370, (0 missing)
##       reimbursement2008 < 355    to the right, improve=0.9835129, (0 missing)
##       depression        < 0.5    to the right, improve=0.3524686, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.3137783, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.2903122, (0 missing)
## 
## Node number 43: 341 observations
##   predicted class=B1  expected loss=0.2492669  P(node) =0.01705
##     class counts:   256    50    26     8     1
##    probabilities: 0.751 0.147 0.076 0.023 0.003 
## 
## Node number 44: 951 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2197687  P(node) =0.04755
##     class counts:   742   132    48    26     3
##    probabilities: 0.780 0.139 0.050 0.027 0.003 
##   left son=88 (811 obs) right son=89 (140 obs)
##   Primary splits:
##       alzheimers    < 0.5    to the left,  improve=1.2963180, (0 missing)
##       depression    < 0.5    to the left,  improve=1.1750410, (0 missing)
##       kidney        < 0.5    to the left,  improve=0.8204364, (0 missing)
##       diabetes      < 0.5    to the left,  improve=0.8186009, (0 missing)
##       heart.failure < 0.5    to the left,  improve=0.6649241, (0 missing)
## 
## Node number 45: 771 observations,    complexity param=0.0001303838
##   predicted class=B1  expected loss=0.2788586  P(node) =0.03855
##     class counts:   556   129    59    25     2
##    probabilities: 0.721 0.167 0.077 0.032 0.003 
##   left son=90 (758 obs) right son=91 (13 obs)
##   Primary splits:
##       stroke       < 0.5    to the left,  improve=2.8198560, (0 missing)
##       osteoporosis < 0.5    to the left,  improve=1.3510390, (0 missing)
##       age          < 67.5   to the right, improve=1.2269310, (0 missing)
##       diabetes     < 0.5    to the left,  improve=0.9157286, (0 missing)
##       kidney       < 0.5    to the left,  improve=0.7050616, (0 missing)
## 
## Node number 46: 771 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.2853437  P(node) =0.03855
##     class counts:   551   139    60    17     4
##    probabilities: 0.715 0.180 0.078 0.022 0.005 
##   left son=92 (713 obs) right son=93 (58 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=2.3312380, (0 missing)
##       reimbursement2008 < 1465   to the left,  improve=1.5865660, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.3286190, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.1740950, (0 missing)
##       age               < 39.5   to the right, improve=0.8807352, (0 missing)
## 
## Node number 47: 819 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.3638584  P(node) =0.04095
##     class counts:   521   186    74    36     2
##    probabilities: 0.636 0.227 0.090 0.044 0.002 
##   left son=94 (412 obs) right son=95 (407 obs)
##   Primary splits:
##       reimbursement2008 < 1155   to the left,  improve=4.0618270, (0 missing)
##       age               < 96.5   to the left,  improve=1.8771670, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.1124860, (0 missing)
##       depression        < 0.5    to the left,  improve=0.8927430, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.8149295, (0 missing)
##   Surrogate splits:
##       depression    < 0.5    to the left,  agree=0.537, adj=0.069, (0 split)
##       arthritis     < 0.5    to the left,  agree=0.535, adj=0.064, (0 split)
##       age           < 75.5   to the right, agree=0.530, adj=0.054, (0 split)
##       copd          < 0.5    to the left,  agree=0.523, adj=0.039, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.521, adj=0.037, (0 split)
## 
## Node number 48: 680 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.3441176  P(node) =0.034
##     class counts:   446   153    59    20     2
##    probabilities: 0.656 0.225 0.087 0.029 0.003 
##   left son=96 (524 obs) right son=97 (156 obs)
##   Primary splits:
##       reimbursement2008 < 2605   to the left,  improve=2.7829410, (0 missing)
##       age               < 96.5   to the left,  improve=1.1143550, (0 missing)
##       copd              < 0.5    to the left,  improve=1.0550180, (0 missing)
##       depression        < 0.5    to the left,  improve=1.0401960, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.9369192, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.865, adj=0.41, (0 split)
## 
## Node number 49: 261 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.4750958  P(node) =0.01305
##     class counts:   137    76    37     9     2
##    probabilities: 0.525 0.291 0.142 0.034 0.008 
##   left son=98 (110 obs) right son=99 (151 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=2.985889, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.377857, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.334625, (0 missing)
##       reimbursement2008 < 3285   to the right, improve=1.198129, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.099034, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1845   to the left,  agree=0.613, adj=0.082, (0 split)
## 
## Node number 50: 82 observations,    complexity param=0.0006084576
##   predicted class=B1  expected loss=0.4634146  P(node) =0.0041
##     class counts:    44    22    12     4     0
##    probabilities: 0.537 0.268 0.146 0.049 0.000 
##   left son=100 (63 obs) right son=101 (19 obs)
##   Primary splits:
##       age               < 63.5   to the right, improve=2.9141960, (0 missing)
##       reimbursement2008 < 3080   to the right, improve=1.7365850, (0 missing)
##       copd              < 0.5    to the left,  improve=1.5828040, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.0929760, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.7827975, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1615   to the right, agree=0.78, adj=0.053, (0 split)
## 
## Node number 51: 64 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.5625  P(node) =0.0032
##     class counts:    18    28    15     3     0
##    probabilities: 0.281 0.438 0.234 0.047 0.000 
##   left son=102 (28 obs) right son=103 (36 obs)
##   Primary splits:
##       age               < 84.5   to the right, improve=2.3010910, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.1798210, (0 missing)
##       reimbursement2008 < 2345   to the left,  improve=0.9276332, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.6452851, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5431399, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1595   to the left,  agree=0.594, adj=0.071, (0 split)
##       depression        < 0.5    to the right, agree=0.578, adj=0.036, (0 split)
## 
## Node number 52: 880 observations,    complexity param=0.0004563432
##   predicted class=B1  expected loss=0.4681818  P(node) =0.044
##     class counts:   468   257   102    46     7
##    probabilities: 0.532 0.292 0.116 0.052 0.008 
##   left son=104 (849 obs) right son=105 (31 obs)
##   Primary splits:
##       stroke            < 0.5    to the left,  improve=3.387993, (0 missing)
##       age               < 73.5   to the right, improve=3.306641, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=3.159084, (0 missing)
##       copd              < 0.5    to the left,  improve=2.787275, (0 missing)
##       reimbursement2008 < 1855   to the left,  improve=2.780152, (0 missing)
## 
## Node number 53: 395 observations,    complexity param=0.001064801
##   predicted class=B1  expected loss=0.5696203  P(node) =0.01975
##     class counts:   170   152    50    22     1
##    probabilities: 0.430 0.385 0.127 0.056 0.003 
##   left son=106 (80 obs) right son=107 (315 obs)
##   Primary splits:
##       age               < 84.5   to the right, improve=3.498056, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=2.462798, (0 missing)
##       reimbursement2008 < 1760   to the left,  improve=2.298825, (0 missing)
##       cancer            < 0.5    to the left,  improve=2.009374, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.079384, (0 missing)
## 
## Node number 54: 614 observations,    complexity param=0.002053544
##   predicted class=B1  expected loss=0.5684039  P(node) =0.0307
##     class counts:   265   216    94    37     2
##    probabilities: 0.432 0.352 0.153 0.060 0.003 
##   left son=108 (317 obs) right son=109 (297 obs)
##   Primary splits:
##       heart.failure < 0.5    to the left,  improve=5.706356, (0 missing)
##       cancer        < 0.5    to the left,  improve=3.620611, (0 missing)
##       kidney        < 0.5    to the left,  improve=2.718926, (0 missing)
##       diabetes      < 0.5    to the left,  improve=2.388979, (0 missing)
##       stroke        < 0.5    to the left,  improve=2.007035, (0 missing)
##   Surrogate splits:
##       diabetes   < 0.5    to the left,  agree=0.593, adj=0.158, (0 split)
##       copd       < 0.5    to the left,  agree=0.570, adj=0.111, (0 split)
##       kidney     < 0.5    to the left,  agree=0.559, adj=0.088, (0 split)
##       age        < 86.5   to the left,  agree=0.550, adj=0.071, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.542, adj=0.054, (0 split)
## 
## Node number 55: 286 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.493007  P(node) =0.0143
##     class counts:    79   145    46    14     2
##    probabilities: 0.276 0.507 0.161 0.049 0.007 
##   left son=110 (174 obs) right son=111 (112 obs)
##   Primary splits:
##       reimbursement2008 < 3015   to the left,  improve=3.399972, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=2.660008, (0 missing)
##       copd              < 0.5    to the left,  improve=1.954436, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.720664, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.503497, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.972, adj=0.929, (0 split)
##       age        < 47.5   to the right, agree=0.612, adj=0.009, (0 split)
## 
## Node number 56: 563 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.4476021  P(node) =0.02815
##     class counts:   311   158    71    20     3
##    probabilities: 0.552 0.281 0.126 0.036 0.005 
##   left son=112 (419 obs) right son=113 (144 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=4.749310, (0 missing)
##       ihd               < 0.5    to the left,  improve=4.117879, (0 missing)
##       reimbursement2008 < 8450   to the right, improve=2.969907, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=2.407056, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=2.354174, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 3465   to the right, agree=0.746, adj=0.007, (0 split)
## 
## Node number 57: 119 observations,    complexity param=0.0009126863
##   predicted class=B2  expected loss=0.6302521  P(node) =0.00595
##     class counts:    36    44    26    13     0
##    probabilities: 0.303 0.370 0.218 0.109 0.000 
##   left son=114 (55 obs) right son=115 (64 obs)
##   Primary splits:
##       reimbursement2008 < 6095   to the left,  improve=1.638928, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.623836, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.588552, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.103598, (0 missing)
##       copd              < 0.5    to the left,  improve=1.082200, (0 missing)
##   Surrogate splits:
##       bucket2008    < 2.5    to the left,  agree=0.798, adj=0.564, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.689, adj=0.327, (0 split)
##       ihd           < 0.5    to the left,  agree=0.655, adj=0.255, (0 split)
##       age           < 72.5   to the left,  agree=0.580, adj=0.091, (0 split)
##       kidney        < 0.5    to the left,  agree=0.580, adj=0.091, (0 split)
## 
## Node number 58: 213 observations,    complexity param=0.0008619815
##   predicted class=B2  expected loss=0.6056338  P(node) =0.01065
##     class counts:    75    84    42    12     0
##    probabilities: 0.352 0.394 0.197 0.056 0.000 
##   left son=116 (20 obs) right son=117 (193 obs)
##   Primary splits:
##       age               < 55.5   to the left,  improve=2.485799, (0 missing)
##       reimbursement2008 < 9080   to the right, improve=1.923864, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.913762, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.732394, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.683900, (0 missing)
## 
## Node number 59: 107 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.5700935  P(node) =0.00535
##     class counts:    22    46    30     9     0
##    probabilities: 0.206 0.430 0.280 0.084 0.000 
##   left son=118 (13 obs) right son=119 (94 obs)
##   Primary splits:
##       reimbursement2008 < 25420  to the right, improve=1.3314010, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.1104610, (0 missing)
##       age               < 87.5   to the left,  improve=0.9520085, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.6222856, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.6046879, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.953, adj=0.615, (0 split)
## 
## Node number 60: 964 observations,    complexity param=0.0008746577
##   predicted class=B2  expected loss=0.5923237  P(node) =0.0482
##     class counts:   324   393   182    60     5
##    probabilities: 0.336 0.408 0.189 0.062 0.005 
##   left son=120 (791 obs) right son=121 (173 obs)
##   Primary splits:
##       cancer            < 0.5    to the left,  improve=7.881057, (0 missing)
##       age               < 70.5   to the left,  improve=5.309810, (0 missing)
##       reimbursement2008 < 58515  to the left,  improve=5.164127, (0 missing)
##       bucket2008        < 4.5    to the left,  improve=4.128531, (0 missing)
##       ihd               < 0.5    to the left,  improve=3.548552, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 70655  to the left,  agree=0.823, adj=0.012, (0 split)
## 
## Node number 61: 604 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5115894  P(node) =0.0302
##     class counts:   124   295   122    57     6
##    probabilities: 0.205 0.488 0.202 0.094 0.010 
##   left son=122 (69 obs) right son=123 (535 obs)
##   Primary splits:
##       reimbursement2008 < 3875   to the left,  improve=3.786294, (0 missing)
##       depression        < 0.5    to the left,  improve=2.941959, (0 missing)
##       age               < 34     to the right, improve=1.969721, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.555014, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.351079, (0 missing)
## 
## Node number 62: 1090 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.5752294  P(node) =0.0545
##     class counts:   195   463   261   148    23
##    probabilities: 0.179 0.425 0.239 0.136 0.021 
##   left son=124 (638 obs) right son=125 (452 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=7.151203, (0 missing)
##       reimbursement2008 < 5655   to the left,  improve=3.223904, (0 missing)
##       ihd               < 0.5    to the left,  improve=2.644429, (0 missing)
##       age               < 44.5   to the right, improve=2.630564, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.756050, (0 missing)
##   Surrogate splits:
##       age < 29.5   to the right, agree=0.589, adj=0.009, (0 split)
## 
## Node number 63: 936 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6388889  P(node) =0.0468
##     class counts:   119   338   207   229    43
##    probabilities: 0.127 0.361 0.221 0.245 0.046 
##   left son=126 (53 obs) right son=127 (883 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=2.996452, (0 missing)
##       reimbursement2008 < 26375  to the left,  improve=2.908218, (0 missing)
##       age               < 65.5   to the right, improve=2.302986, (0 missing)
##       copd              < 0.5    to the left,  improve=2.090686, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.919244, (0 missing)
## 
## Node number 80: 1764 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1485261  P(node) =0.0882
##     class counts:  1502   162    75    22     3
##    probabilities: 0.851 0.092 0.043 0.012 0.002 
##   left son=160 (1586 obs) right son=161 (178 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=0.9323517, (0 missing)
##       age               < 71.5   to the left,  improve=0.7839176, (0 missing)
##       reimbursement2008 < 665    to the left,  improve=0.6933809, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5712541, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5496311, (0 missing)
## 
## Node number 81: 10 observations
##   predicted class=B1  expected loss=0.4  P(node) =0.0005
##     class counts:     6     3     0     1     0
##    probabilities: 0.600 0.300 0.000 0.100 0.000 
## 
## Node number 84: 147 observations
##   predicted class=B1  expected loss=0.122449  P(node) =0.00735
##     class counts:   129     9     7     2     0
##    probabilities: 0.878 0.061 0.048 0.014 0.000 
## 
## Node number 85: 26 observations,    complexity param=5.07048e-05
##   predicted class=B1  expected loss=0.3846154  P(node) =0.0013
##     class counts:    16     4     4     2     0
##    probabilities: 0.615 0.154 0.154 0.077 0.000 
##   left son=170 (19 obs) right son=171 (7 obs)
##   Primary splits:
##       reimbursement2008 < 250    to the right, improve=1.9872760, (0 missing)
##       age               < 56.5   to the left,  improve=0.3934732, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.3076923, (0 missing)
## 
## Node number 88: 811 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2083847  P(node) =0.04055
##     class counts:   642   105    38    24     2
##    probabilities: 0.792 0.129 0.047 0.030 0.002 
##   left son=176 (544 obs) right son=177 (267 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=1.0063530, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9333841, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.7386915, (0 missing)
##       reimbursement2008 < 905    to the left,  improve=0.5328549, (0 missing)
##       age               < 95     to the right, improve=0.4748885, (0 missing)
##   Surrogate splits:
##       kidney            < 0.5    to the left,  agree=0.691, adj=0.060, (0 split)
##       copd              < 0.5    to the left,  agree=0.684, adj=0.041, (0 split)
##       reimbursement2008 < 1075   to the left,  agree=0.677, adj=0.019, (0 split)
##       stroke            < 0.5    to the left,  agree=0.676, adj=0.015, (0 split)
##       age               < 98.5   to the left,  agree=0.672, adj=0.004, (0 split)
## 
## Node number 89: 140 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2857143  P(node) =0.007
##     class counts:   100    27    10     2     1
##    probabilities: 0.714 0.193 0.071 0.014 0.007 
##   left son=178 (133 obs) right son=179 (7 obs)
##   Primary splits:
##       age               < 91.5   to the left,  improve=1.9225560, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.7529606, (0 missing)
##       reimbursement2008 < 715    to the left,  improve=0.6604396, (0 missing)
##       copd              < 0.5    to the right, improve=0.5219780, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.5090226, (0 missing)
## 
## Node number 90: 758 observations,    complexity param=0.0001303838
##   predicted class=B1  expected loss=0.2730871  P(node) =0.0379
##     class counts:   551   126    54    25     2
##    probabilities: 0.727 0.166 0.071 0.033 0.003 
##   left son=180 (586 obs) right son=181 (172 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=1.4527870, (0 missing)
##       age               < 67.5   to the right, improve=1.2745370, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.1236350, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.8891357, (0 missing)
##       reimbursement2008 < 1125   to the right, improve=0.6899320, (0 missing)
## 
## Node number 91: 13 observations
##   predicted class=B1  expected loss=0.6153846  P(node) =0.00065
##     class counts:     5     3     5     0     0
##    probabilities: 0.385 0.231 0.385 0.000 0.000 
## 
## Node number 92: 713 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.2720898  P(node) =0.03565
##     class counts:   519   125    51    14     4
##    probabilities: 0.728 0.175 0.072 0.020 0.006 
##   left son=184 (691 obs) right son=185 (22 obs)
##   Primary splits:
##       age               < 39.5   to the right, improve=1.1668370, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.1390500, (0 missing)
##       reimbursement2008 < 1465   to the left,  improve=0.9813589, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.5722300, (0 missing)
##       cancer            < 0.5    to the right, improve=0.3196481, (0 missing)
## 
## Node number 93: 58 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4482759  P(node) =0.0029
##     class counts:    32    14     9     3     0
##    probabilities: 0.552 0.241 0.155 0.052 0.000 
##   left son=186 (15 obs) right son=187 (43 obs)
##   Primary splits:
##       age               < 69.5   to the left,  improve=3.2494520, (0 missing)
##       arthritis         < 0.5    to the left,  improve=2.0076310, (0 missing)
##       reimbursement2008 < 1420   to the left,  improve=1.5737930, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7189879, (0 missing)
##       depression        < 0.5    to the right, improve=0.5328407, (0 missing)
## 
## Node number 94: 412 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3058252  P(node) =0.0206
##     class counts:   286    79    34    12     1
##    probabilities: 0.694 0.192 0.083 0.029 0.002 
##   left son=188 (90 obs) right son=189 (322 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=1.7905600, (0 missing)
##       kidney            < 0.5    to the right, improve=1.1304480, (0 missing)
##       reimbursement2008 < 845    to the right, improve=1.0921920, (0 missing)
##       age               < 46.5   to the right, improve=0.8862043, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.6585376, (0 missing)
## 
## Node number 95: 407 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4226044  P(node) =0.02035
##     class counts:   235   107    40    24     1
##    probabilities: 0.577 0.263 0.098 0.059 0.002 
##   left son=190 (382 obs) right son=191 (25 obs)
##   Primary splits:
##       age               < 89.5   to the left,  improve=2.713552, (0 missing)
##       reimbursement2008 < 1175   to the right, improve=1.792258, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.783573, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.289334, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.141444, (0 missing)
## 
## Node number 96: 524 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.3282443  P(node) =0.0262
##     class counts:   352   103    52    16     1
##    probabilities: 0.672 0.197 0.099 0.031 0.002 
##   left son=192 (517 obs) right son=193 (7 obs)
##   Primary splits:
##       age               < 96.5   to the left,  improve=1.6925650, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.3207170, (0 missing)
##       depression        < 0.5    to the left,  improve=1.3189090, (0 missing)
##       copd              < 0.5    to the left,  improve=1.0179070, (0 missing)
##       reimbursement2008 < 2555   to the right, improve=0.9997021, (0 missing)
## 
## Node number 97: 156 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.3974359  P(node) =0.0078
##     class counts:    94    50     7     4     1
##    probabilities: 0.603 0.321 0.045 0.026 0.006 
##   left son=194 (118 obs) right son=195 (38 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=3.3295250, (0 missing)
##       age               < 71.5   to the left,  improve=1.4519230, (0 missing)
##       reimbursement2008 < 2805   to the right, improve=1.4487180, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.1881170, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4811752, (0 missing)
## 
## Node number 98: 110 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.3818182  P(node) =0.0055
##     class counts:    68    26     9     6     1
##    probabilities: 0.618 0.236 0.082 0.055 0.009 
##   left son=196 (32 obs) right son=197 (78 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=1.5659670, (0 missing)
##       reimbursement2008 < 1805   to the right, improve=1.4835180, (0 missing)
##       age               < 65     to the left,  improve=1.0413730, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.8202845, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.5535759, (0 missing)
##   Surrogate splits:
##       copd       < 0.5    to the right, agree=0.727, adj=0.063, (0 split)
##       age        < 87.5   to the right, agree=0.718, adj=0.031, (0 split)
##       alzheimers < 0.5    to the right, agree=0.718, adj=0.031, (0 split)
## 
## Node number 99: 151 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.5430464  P(node) =0.00755
##     class counts:    69    50    28     3     1
##    probabilities: 0.457 0.331 0.185 0.020 0.007 
##   left son=198 (140 obs) right son=199 (11 obs)
##   Primary splits:
##       reimbursement2008 < 1675   to the right, improve=1.6192660, (0 missing)
##       age               < 79.5   to the left,  improve=1.2019600, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.1347180, (0 missing)
##       arthritis         < 0.5    to the right, improve=1.0828460, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.7387061, (0 missing)
## 
## Node number 100: 63 observations
##   predicted class=B1  expected loss=0.3968254  P(node) =0.00315
##     class counts:    38    12     9     4     0
##    probabilities: 0.603 0.190 0.143 0.063 0.000 
## 
## Node number 101: 19 observations
##   predicted class=B2  expected loss=0.4736842  P(node) =0.00095
##     class counts:     6    10     3     0     0
##    probabilities: 0.316 0.526 0.158 0.000 0.000 
## 
## Node number 102: 28 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.0014
##     class counts:     9    16     2     1     0
##    probabilities: 0.321 0.571 0.071 0.036 0.000 
## 
## Node number 103: 36 observations,    complexity param=0.000507048
##   predicted class=B3  expected loss=0.6388889  P(node) =0.0018
##     class counts:     9    12    13     2     0
##    probabilities: 0.250 0.333 0.361 0.056 0.000 
##   left son=206 (10 obs) right son=207 (26 obs)
##   Primary splits:
##       reimbursement2008 < 1990   to the left,  improve=2.3444440, (0 missing)
##       age               < 78.5   to the left,  improve=1.6694440, (0 missing)
##       depression        < 0.5    to the right, improve=1.5277780, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.9801587, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3518519, (0 missing)
## 
## Node number 104: 849 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.459364  P(node) =0.04245
##     class counts:   459   246    92    45     7
##    probabilities: 0.541 0.290 0.108 0.053 0.008 
##   left son=208 (406 obs) right son=209 (443 obs)
##   Primary splits:
##       age               < 73.5   to the right, improve=4.000432, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=3.247702, (0 missing)
##       reimbursement2008 < 1855   to the left,  improve=2.540980, (0 missing)
##       kidney            < 0.5    to the left,  improve=2.518808, (0 missing)
##       copd              < 0.5    to the left,  improve=2.326450, (0 missing)
##   Surrogate splits:
##       osteoporosis      < 0.5    to the right, agree=0.541, adj=0.039, (0 split)
##       reimbursement2008 < 2215   to the right, agree=0.537, adj=0.032, (0 split)
##       heart.failure     < 0.5    to the right, agree=0.527, adj=0.010, (0 split)
## 
## Node number 105: 31 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6451613  P(node) =0.00155
##     class counts:     9    11    10     1     0
##    probabilities: 0.290 0.355 0.323 0.032 0.000 
##   left son=210 (17 obs) right son=211 (14 obs)
##   Primary splits:
##       age               < 75.5   to the right, improve=1.5871510, (0 missing)
##       reimbursement2008 < 2370   to the left,  improve=1.1497190, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5679117, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.5234255, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.3567588, (0 missing)
##   Surrogate splits:
##       osteoporosis      < 0.5    to the left,  agree=0.677, adj=0.286, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.581, adj=0.071, (0 split)
##       kidney            < 0.5    to the left,  agree=0.581, adj=0.071, (0 split)
##       reimbursement2008 < 2035   to the right, agree=0.581, adj=0.071, (0 split)
## 
## Node number 106: 80 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.425  P(node) =0.004
##     class counts:    46    23     5     6     0
##    probabilities: 0.575 0.287 0.062 0.075 0.000 
##   left son=212 (55 obs) right son=213 (25 obs)
##   Primary splits:
##       age               < 93.5   to the left,  improve=2.611364, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.487349, (0 missing)
##       reimbursement2008 < 2125   to the right, improve=1.457423, (0 missing)
##       stroke            < 0.5    to the right, improve=1.369444, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.209632, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.7, adj=0.04, (0 split)
## 
## Node number 107: 315 observations,    complexity param=0.001064801
##   predicted class=B2  expected loss=0.5904762  P(node) =0.01575
##     class counts:   124   129    45    16     1
##    probabilities: 0.394 0.410 0.143 0.051 0.003 
##   left son=214 (298 obs) right son=215 (17 obs)
##   Primary splits:
##       cancer            < 0.5    to the left,  improve=2.959923, (0 missing)
##       age               < 71.5   to the left,  improve=2.862764, (0 missing)
##       reimbursement2008 < 1705   to the left,  improve=2.440816, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.340605, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.203641, (0 missing)
## 
## Node number 108: 317 observations,    complexity param=0.002053544
##   predicted class=B1  expected loss=0.488959  P(node) =0.01585
##     class counts:   162   100    41    12     2
##    probabilities: 0.511 0.315 0.129 0.038 0.006 
##   left son=216 (281 obs) right son=217 (36 obs)
##   Primary splits:
##       cancer            < 0.5    to the left,  improve=7.0540640, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.2948500, (0 missing)
##       age               < 67.5   to the left,  improve=1.1694920, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7114914, (0 missing)
##       reimbursement2008 < 3375   to the right, improve=0.7111587, (0 missing)
## 
## Node number 109: 297 observations,    complexity param=0.001216915
##   predicted class=B2  expected loss=0.6094276  P(node) =0.01485
##     class counts:   103   116    53    25     0
##    probabilities: 0.347 0.391 0.178 0.084 0.000 
##   left son=218 (213 obs) right son=219 (84 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=3.189782, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=2.501684, (0 missing)
##       stroke            < 0.5    to the left,  improve=2.034430, (0 missing)
##       reimbursement2008 < 2545   to the right, improve=1.945862, (0 missing)
##       copd              < 0.5    to the left,  improve=1.405257, (0 missing)
## 
## Node number 110: 174 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5574713  P(node) =0.0087
##     class counts:    54    77    36     6     1
##    probabilities: 0.310 0.443 0.207 0.034 0.006 
##   left son=220 (157 obs) right son=221 (17 obs)
##   Primary splits:
##       reimbursement2008 < 2965   to the left,  improve=2.237107, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.712199, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.626229, (0 missing)
##       age               < 66.5   to the left,  improve=1.521372, (0 missing)
##       copd              < 0.5    to the left,  improve=1.472441, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.948, adj=0.471, (0 split)
## 
## Node number 111: 112 observations,    complexity param=0.000190143
##   predicted class=B2  expected loss=0.3928571  P(node) =0.0056
##     class counts:    25    68    10     8     1
##    probabilities: 0.223 0.607 0.089 0.071 0.009 
##   left son=222 (81 obs) right son=223 (31 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=2.8140400, (0 missing)
##       age               < 88.5   to the left,  improve=1.5837910, (0 missing)
##       reimbursement2008 < 3405   to the left,  improve=1.3337910, (0 missing)
##       copd              < 0.5    to the left,  improve=1.0054300, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.8988095, (0 missing)
## 
## Node number 112: 419 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.4033413  P(node) =0.02095
##     class counts:   250   111    42    13     3
##    probabilities: 0.597 0.265 0.100 0.031 0.007 
##   left son=224 (330 obs) right son=225 (89 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=2.610752, (0 missing)
##       reimbursement2008 < 8430   to the right, improve=2.207527, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.748820, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.716918, (0 missing)
##       copd              < 0.5    to the left,  improve=1.485559, (0 missing)
## 
## Node number 113: 144 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.5763889  P(node) =0.0072
##     class counts:    61    47    29     7     0
##    probabilities: 0.424 0.326 0.201 0.049 0.000 
##   left son=226 (58 obs) right son=227 (86 obs)
##   Primary splits:
##       age               < 73.5   to the left,  improve=2.071126, (0 missing)
##       reimbursement2008 < 3585   to the right, improve=2.059784, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.866475, (0 missing)
##       copd              < 0.5    to the right, improve=1.815446, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.213565, (0 missing)
##   Surrogate splits:
##       ihd               < 0.5    to the left,  agree=0.604, adj=0.017, (0 split)
##       reimbursement2008 < 25970  to the right, agree=0.604, adj=0.017, (0 split)
## 
## Node number 114: 55 observations,    complexity param=0.000760572
##   predicted class=B1  expected loss=0.6181818  P(node) =0.00275
##     class counts:    21    15    12     7     0
##    probabilities: 0.382 0.273 0.218 0.127 0.000 
##   left son=228 (42 obs) right son=229 (13 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=4.3525140, (0 missing)
##       copd              < 0.5    to the left,  improve=1.5063600, (0 missing)
##       reimbursement2008 < 3745   to the left,  improve=1.2449130, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.0678650, (0 missing)
##       age               < 64.5   to the left,  improve=0.7169246, (0 missing)
##   Surrogate splits:
##       age < 94     to the left,  agree=0.782, adj=0.077, (0 split)
## 
## Node number 115: 64 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.546875  P(node) =0.0032
##     class counts:    15    29    14     6     0
##    probabilities: 0.234 0.453 0.219 0.094 0.000 
##   left son=230 (41 obs) right son=231 (23 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.4228860, (0 missing)
##       reimbursement2008 < 9080   to the right, improve=1.9265930, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=1.1557870, (0 missing)
##       age               < 66.5   to the right, improve=1.0320330, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.7558656, (0 missing)
##   Surrogate splits:
##       age               < 61     to the right, agree=0.672, adj=0.087, (0 split)
##       reimbursement2008 < 6480   to the right, agree=0.656, adj=0.043, (0 split)
## 
## Node number 116: 20 observations
##   predicted class=B1  expected loss=0.45  P(node) =0.001
##     class counts:    11     3     6     0     0
##    probabilities: 0.550 0.150 0.300 0.000 0.000 
## 
## Node number 117: 193 observations,    complexity param=0.0008619815
##   predicted class=B2  expected loss=0.5803109  P(node) =0.00965
##     class counts:    64    81    36    12     0
##    probabilities: 0.332 0.420 0.187 0.062 0.000 
##   left son=234 (136 obs) right son=235 (57 obs)
##   Primary splits:
##       age               < 82.5   to the left,  improve=2.821502, (0 missing)
##       cancer            < 0.5    to the left,  improve=2.768983, (0 missing)
##       reimbursement2008 < 8080   to the right, improve=2.356612, (0 missing)
##       bucket2008        < 2.5    to the right, improve=2.356612, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=2.157632, (0 missing)
## 
## Node number 118: 13 observations
##   predicted class=B3  expected loss=0.5384615  P(node) =0.00065
##     class counts:     4     3     6     0     0
##    probabilities: 0.308 0.231 0.462 0.000 0.000 
## 
## Node number 119: 94 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.5425532  P(node) =0.0047
##     class counts:    18    43    24     9     0
##    probabilities: 0.191 0.457 0.255 0.096 0.000 
##   left son=238 (8 obs) right son=239 (86 obs)
##   Primary splits:
##       reimbursement2008 < 17845  to the right, improve=2.4226870, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.0548490, (0 missing)
##       age               < 76.5   to the left,  improve=0.9148936, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.8079343, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7191072, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.968, adj=0.625, (0 split)
## 
## Node number 120: 791 observations,    complexity param=0.0008746577
##   predicted class=B2  expected loss=0.5979772  P(node) =0.03955
##     class counts:   292   318   129    48     4
##    probabilities: 0.369 0.402 0.163 0.061 0.005 
##   left son=240 (277 obs) right son=241 (514 obs)
##   Primary splits:
##       age               < 70.5   to the left,  improve=3.355752, (0 missing)
##       reimbursement2008 < 49845  to the left,  improve=3.229908, (0 missing)
##       ihd               < 0.5    to the left,  improve=2.761119, (0 missing)
##       copd              < 0.5    to the left,  improve=2.003968, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.265923, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 3445   to the left,  agree=0.655, adj=0.014, (0 split)
## 
## Node number 121: 173 observations,    complexity param=0.0005324004
##   predicted class=B2  expected loss=0.566474  P(node) =0.00865
##     class counts:    32    75    53    12     1
##    probabilities: 0.185 0.434 0.306 0.069 0.006 
##   left son=242 (39 obs) right son=243 (134 obs)
##   Primary splits:
##       age               < 82.5   to the right, improve=5.0010880, (0 missing)
##       reimbursement2008 < 6630   to the left,  improve=2.0288640, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.2040470, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.8841145, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8253101, (0 missing)
## 
## Node number 122: 69 observations
##   predicted class=B2  expected loss=0.3188406  P(node) =0.00345
##     class counts:    10    47     9     3     0
##    probabilities: 0.145 0.681 0.130 0.043 0.000 
## 
## Node number 123: 535 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5364486  P(node) =0.02675
##     class counts:   114   248   113    54     6
##    probabilities: 0.213 0.464 0.211 0.101 0.011 
##   left son=246 (282 obs) right son=247 (253 obs)
##   Primary splits:
##       depression   < 0.5    to the left,  improve=2.483857, (0 missing)
##       age          < 34     to the right, improve=2.414565, (0 missing)
##       alzheimers   < 0.5    to the left,  improve=1.680399, (0 missing)
##       osteoporosis < 0.5    to the left,  improve=1.549482, (0 missing)
##       ihd          < 0.5    to the left,  improve=1.112006, (0 missing)
##   Surrogate splits:
##       age               < 63.5   to the right, agree=0.574, adj=0.099, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.574, adj=0.099, (0 split)
##       reimbursement2008 < 8115   to the left,  agree=0.574, adj=0.099, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.568, adj=0.087, (0 split)
##       stroke            < 0.5    to the left,  agree=0.536, adj=0.020, (0 split)
## 
## Node number 124: 638 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.630094  P(node) =0.0319
##     class counts:   139   236   154    93    16
##    probabilities: 0.218 0.370 0.241 0.146 0.025 
##   left son=248 (612 obs) right son=249 (26 obs)
##   Primary splits:
##       age               < 44.5   to the right, improve=4.240890, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.955476, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.928245, (0 missing)
##       reimbursement2008 < 6575   to the right, improve=1.687162, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.121735, (0 missing)
## 
## Node number 125: 452 observations,    complexity param=0.0002028192
##   predicted class=B2  expected loss=0.4977876  P(node) =0.0226
##     class counts:    56   227   107    55     7
##    probabilities: 0.124 0.502 0.237 0.122 0.015 
##   left son=250 (143 obs) right son=251 (309 obs)
##   Primary splits:
##       reimbursement2008 < 5300   to the left,  improve=3.3421300, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.7850810, (0 missing)
##       age               < 39     to the left,  improve=1.2021390, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.9484846, (0 missing)
##       copd              < 0.5    to the left,  improve=0.7242827, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.715, adj=0.098, (0 split)
##       age        < 99.5   to the right, agree=0.686, adj=0.007, (0 split)
## 
## Node number 126: 53 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6603774  P(node) =0.00265
##     class counts:    16    18     4    14     1
##    probabilities: 0.302 0.340 0.075 0.264 0.019 
##   left son=252 (20 obs) right son=253 (33 obs)
##   Primary splits:
##       reimbursement2008 < 25800  to the right, improve=2.686221, (0 missing)
##       stroke            < 0.5    to the right, improve=1.745810, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.708468, (0 missing)
##       cancer            < 0.5    to the right, improve=1.513346, (0 missing)
##       copd              < 0.5    to the right, improve=1.510950, (0 missing)
##   Surrogate splits:
##       bucket2008    < 4.5    to the right, agree=0.679, adj=0.15, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.660, adj=0.10, (0 split)
## 
## Node number 127: 883 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6375991  P(node) =0.04415
##     class counts:   103   320   203   215    42
##    probabilities: 0.117 0.362 0.230 0.243 0.048 
##   left son=254 (396 obs) right son=255 (487 obs)
##   Primary splits:
##       reimbursement2008 < 26375  to the left,  improve=3.823201, (0 missing)
##       age               < 65.5   to the right, improve=2.689667, (0 missing)
##       copd              < 0.5    to the left,  improve=1.850928, (0 missing)
##       depression        < 0.5    to the left,  improve=1.564142, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=1.541530, (0 missing)
##   Surrogate splits:
##       bucket2008    < 3.5    to the left,  agree=0.736, adj=0.412, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.576, adj=0.056, (0 split)
##       copd          < 0.5    to the left,  agree=0.564, adj=0.028, (0 split)
## 
## Node number 160: 1586 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1431274  P(node) =0.0793
##     class counts:  1359   137    68    19     3
##    probabilities: 0.857 0.086 0.043 0.012 0.002 
##   left son=320 (756 obs) right son=321 (830 obs)
##   Primary splits:
##       age               < 71.5   to the left,  improve=0.9232109, (0 missing)
##       reimbursement2008 < 665    to the left,  improve=0.6940889, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6379602, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.5784235, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5106421, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 655    to the right, agree=0.530, adj=0.015, (0 split)
##       depression        < 0.5    to the right, agree=0.529, adj=0.012, (0 split)
##       copd              < 0.5    to the right, agree=0.528, adj=0.011, (0 split)
##       stroke            < 0.5    to the right, agree=0.524, adj=0.001, (0 split)
## 
## Node number 161: 178 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1966292  P(node) =0.0089
##     class counts:   143    25     7     3     0
##    probabilities: 0.803 0.140 0.039 0.017 0.000 
##   left son=322 (171 obs) right son=323 (7 obs)
##   Primary splits:
##       reimbursement2008 < 225    to the right, improve=2.3903390, (0 missing)
##       age               < 79.5   to the right, improve=0.6636044, (0 missing)
##       depression        < 0.5    to the right, improve=0.6166862, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.1555824, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.1467316, (0 missing)
## 
## Node number 170: 19 observations
##   predicted class=B1  expected loss=0.2631579  P(node) =0.00095
##     class counts:    14     2     1     2     0
##    probabilities: 0.737 0.105 0.053 0.105 0.000 
## 
## Node number 171: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     2     2     3     0     0
##    probabilities: 0.286 0.286 0.429 0.000 0.000 
## 
## Node number 176: 544 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1930147  P(node) =0.0272
##     class counts:   439    60    26    17     2
##    probabilities: 0.807 0.110 0.048 0.031 0.004 
##   left son=352 (338 obs) right son=353 (206 obs)
##   Primary splits:
##       reimbursement2008 < 905    to the left,  improve=1.0110110, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.9330888, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6888143, (0 missing)
##       age               < 83.5   to the left,  improve=0.6468196, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.4582147, (0 missing)
##   Surrogate splits:
##       age    < 97.5   to the left,  agree=0.629, adj=0.019, (0 split)
##       cancer < 0.5    to the left,  agree=0.627, adj=0.015, (0 split)
##       copd   < 0.5    to the left,  agree=0.623, adj=0.005, (0 split)
## 
## Node number 177: 267 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2397004  P(node) =0.01335
##     class counts:   203    45    12     7     0
##    probabilities: 0.760 0.169 0.045 0.026 0.000 
##   left son=354 (182 obs) right son=355 (85 obs)
##   Primary splits:
##       reimbursement2008 < 795    to the right, improve=1.3274960, (0 missing)
##       age               < 71.5   to the left,  improve=0.8090960, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6076067, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.4599499, (0 missing)
##       cancer            < 0.5    to the right, improve=0.4324521, (0 missing)
## 
## Node number 178: 133 observations
##   predicted class=B1  expected loss=0.2631579  P(node) =0.00665
##     class counts:    98    24     9     1     1
##    probabilities: 0.737 0.180 0.068 0.008 0.008 
## 
## Node number 179: 7 observations
##   predicted class=B2  expected loss=0.5714286  P(node) =0.00035
##     class counts:     2     3     1     1     0
##    probabilities: 0.286 0.429 0.143 0.143 0.000 
## 
## Node number 180: 586 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.2559727  P(node) =0.0293
##     class counts:   436    88    43    19     0
##    probabilities: 0.744 0.150 0.073 0.032 0.000 
##   left son=360 (449 obs) right son=361 (137 obs)
##   Primary splits:
##       age               < 67.5   to the right, improve=1.7267490, (0 missing)
##       copd              < 0.5    to the left,  improve=1.0095940, (0 missing)
##       reimbursement2008 < 1235   to the left,  improve=0.9296137, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.4946966, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.4469803, (0 missing)
## 
## Node number 181: 172 observations,    complexity param=0.0001303838
##   predicted class=B1  expected loss=0.3313953  P(node) =0.0086
##     class counts:   115    38    11     6     2
##    probabilities: 0.669 0.221 0.064 0.035 0.012 
##   left son=362 (143 obs) right son=363 (29 obs)
##   Primary splits:
##       age               < 83.5   to the left,  improve=1.8398370, (0 missing)
##       reimbursement2008 < 1115   to the right, improve=1.5955310, (0 missing)
##       copd              < 0.5    to the right, improve=1.1082360, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.0821000, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.9757667, (0 missing)
## 
## Node number 184: 691 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.2662808  P(node) =0.03455
##     class counts:   507   119    50    13     2
##    probabilities: 0.734 0.172 0.072 0.019 0.003 
##   left son=368 (628 obs) right son=369 (63 obs)
##   Primary splits:
##       reimbursement2008 < 1465   to the left,  improve=1.0827960, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8965233, (0 missing)
##       age               < 50     to the left,  improve=0.7515753, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.5491404, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.4331673, (0 missing)
## 
## Node number 185: 22 observations
##   predicted class=B1  expected loss=0.4545455  P(node) =0.0011
##     class counts:    12     6     1     1     2
##    probabilities: 0.545 0.273 0.045 0.045 0.091 
## 
## Node number 186: 15 observations
##   predicted class=B1  expected loss=0.1333333  P(node) =0.00075
##     class counts:    13     0     2     0     0
##    probabilities: 0.867 0.000 0.133 0.000 0.000 
## 
## Node number 187: 43 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5581395  P(node) =0.00215
##     class counts:    19    14     7     3     0
##    probabilities: 0.442 0.326 0.163 0.070 0.000 
##   left son=374 (35 obs) right son=375 (8 obs)
##   Primary splits:
##       reimbursement2008 < 1355   to the left,  improve=1.9905320, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.3960870, (0 missing)
##       age               < 78.5   to the left,  improve=0.5397797, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4476744, (0 missing)
##       depression        < 0.5    to the right, improve=0.3331424, (0 missing)
##   Surrogate splits:
##       arthritis < 0.5    to the left,  agree=0.837, adj=0.125, (0 split)
## 
## Node number 188: 90 observations
##   predicted class=B1  expected loss=0.2111111  P(node) =0.0045
##     class counts:    71    10     7     2     0
##    probabilities: 0.789 0.111 0.078 0.022 0.000 
## 
## Node number 189: 322 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3322981  P(node) =0.0161
##     class counts:   215    69    27    10     1
##    probabilities: 0.668 0.214 0.084 0.031 0.003 
##   left son=378 (310 obs) right son=379 (12 obs)
##   Primary splits:
##       age               < 46.5   to the right, improve=1.9484870, (0 missing)
##       reimbursement2008 < 1135   to the right, improve=1.2465950, (0 missing)
##       kidney            < 0.5    to the right, improve=0.8858863, (0 missing)
##       copd              < 0.5    to the right, improve=0.5966936, (0 missing)
##       depression        < 0.5    to the left,  improve=0.3370662, (0 missing)
## 
## Node number 190: 382 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4057592  P(node) =0.0191
##     class counts:   227    96    36    22     1
##    probabilities: 0.594 0.251 0.094 0.058 0.003 
##   left son=380 (352 obs) right son=381 (30 obs)
##   Primary splits:
##       reimbursement2008 < 1175   to the right, improve=1.447781, (0 missing)
##       arthritis         < 0.5    to the right, improve=1.260633, (0 missing)
##       depression        < 0.5    to the left,  improve=1.219881, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.175814, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.149973, (0 missing)
## 
## Node number 191: 25 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.56  P(node) =0.00125
##     class counts:     8    11     4     2     0
##    probabilities: 0.320 0.440 0.160 0.080 0.000 
##   left son=382 (7 obs) right son=383 (18 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=2.4349210, (0 missing)
##       age               < 94.5   to the left,  improve=1.3873020, (0 missing)
##       reimbursement2008 < 1490   to the right, improve=0.5936508, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.3138889, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1515   to the right, agree=0.84, adj=0.429, (0 split)
##       osteoporosis      < 0.5    to the right, agree=0.76, adj=0.143, (0 split)
## 
## Node number 192: 517 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3230174  P(node) =0.02585
##     class counts:   350   100    50    16     1
##    probabilities: 0.677 0.193 0.097 0.031 0.002 
##   left son=384 (395 obs) right son=385 (122 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=1.3507060, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.1170580, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9771406, (0 missing)
##       reimbursement2008 < 2555   to the right, improve=0.9492119, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.9266289, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1575   to the right, agree=0.766, adj=0.008, (0 split)
## 
## Node number 193: 7 observations
##   predicted class=B2  expected loss=0.5714286  P(node) =0.00035
##     class counts:     2     3     2     0     0
##    probabilities: 0.286 0.429 0.286 0.000 0.000 
## 
## Node number 194: 118 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.3389831  P(node) =0.0059
##     class counts:    78    31     6     2     1
##    probabilities: 0.661 0.263 0.051 0.017 0.008 
##   left son=388 (45 obs) right son=389 (73 obs)
##   Primary splits:
##       age               < 69.5   to the left,  improve=1.1850730, (0 missing)
##       reimbursement2008 < 3390   to the left,  improve=0.8082435, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4190278, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3093904, (0 missing)
##       cancer            < 0.5    to the right, improve=0.2861896, (0 missing)
##   Surrogate splits:
##       alzheimers < 0.5    to the right, agree=0.653, adj=0.089, (0 split)
##       stroke     < 0.5    to the right, agree=0.636, adj=0.044, (0 split)
## 
## Node number 195: 38 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5  P(node) =0.0019
##     class counts:    16    19     1     2     0
##    probabilities: 0.421 0.500 0.026 0.053 0.000 
##   left son=390 (12 obs) right son=391 (26 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=2.1828610, (0 missing)
##       age               < 82     to the right, improve=1.6698930, (0 missing)
##       reimbursement2008 < 2825   to the right, improve=0.6842105, (0 missing)
##       depression        < 0.5    to the right, improve=0.5608097, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5361943, (0 missing)
##   Surrogate splits:
##       age < 82     to the right, agree=0.763, adj=0.25, (0 split)
## 
## Node number 196: 32 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.0016
##     class counts:    24     4     4     0     0
##    probabilities: 0.750 0.125 0.125 0.000 0.000 
## 
## Node number 197: 78 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.4358974  P(node) =0.0039
##     class counts:    44    22     5     6     1
##    probabilities: 0.564 0.282 0.064 0.077 0.013 
##   left son=394 (20 obs) right son=395 (58 obs)
##   Primary splits:
##       reimbursement2008 < 2685   to the right, improve=1.5277630, (0 missing)
##       age               < 65     to the left,  improve=0.8171683, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7077891, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.4080586, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3333333, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the right, agree=0.846, adj=0.40, (0 split)
##       age        < 59.5   to the left,  agree=0.756, adj=0.05, (0 split)
## 
## Node number 198: 140 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5285714  P(node) =0.007
##     class counts:    66    43    27     3     1
##    probabilities: 0.471 0.307 0.193 0.021 0.007 
##   left son=396 (10 obs) right son=397 (130 obs)
##   Primary splits:
##       reimbursement2008 < 1775   to the left,  improve=1.7076920, (0 missing)
##       age               < 79.5   to the left,  improve=1.3659860, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.3345480, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.9142857, (0 missing)
##       cancer            < 0.5    to the right, improve=0.8461408, (0 missing)
## 
## Node number 199: 11 observations
##   predicted class=B2  expected loss=0.3636364  P(node) =0.00055
##     class counts:     3     7     1     0     0
##    probabilities: 0.273 0.636 0.091 0.000 0.000 
## 
## Node number 206: 10 observations
##   predicted class=B1  expected loss=0.4  P(node) =0.0005
##     class counts:     6     2     2     0     0
##    probabilities: 0.600 0.200 0.200 0.000 0.000 
## 
## Node number 207: 26 observations,    complexity param=0.000507048
##   predicted class=B3  expected loss=0.5769231  P(node) =0.0013
##     class counts:     3    10    11     2     0
##    probabilities: 0.115 0.385 0.423 0.077 0.000 
##   left son=414 (12 obs) right son=415 (14 obs)
##   Primary splits:
##       age               < 78.5   to the left,  improve=2.4047620, (0 missing)
##       depression        < 0.5    to the right, improve=1.7636360, (0 missing)
##       reimbursement2008 < 2405   to the left,  improve=1.4060150, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.0902260, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.4722222, (0 missing)
##   Surrogate splits:
##       arthritis         < 0.5    to the right, agree=0.692, adj=0.333, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.654, adj=0.250, (0 split)
##       cancer            < 0.5    to the right, agree=0.615, adj=0.167, (0 split)
##       diabetes          < 0.5    to the left,  agree=0.615, adj=0.167, (0 split)
##       reimbursement2008 < 2455   to the left,  agree=0.615, adj=0.167, (0 split)
## 
## Node number 208: 406 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.3990148  P(node) =0.0203
##     class counts:   244   105    35    19     3
##    probabilities: 0.601 0.259 0.086 0.047 0.007 
##   left son=416 (307 obs) right son=417 (99 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=1.7269200, (0 missing)
##       age               < 88.5   to the left,  improve=1.5011960, (0 missing)
##       reimbursement2008 < 2465   to the right, improve=1.4952500, (0 missing)
##       cancer            < 0.5    to the right, improve=1.0503980, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8595577, (0 missing)
## 
## Node number 209: 443 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.5146727  P(node) =0.02215
##     class counts:   215   141    57    26     4
##    probabilities: 0.485 0.318 0.129 0.059 0.009 
##   left son=418 (261 obs) right son=419 (182 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=4.055554, (0 missing)
##       diabetes          < 0.5    to the left,  improve=3.280522, (0 missing)
##       kidney            < 0.5    to the left,  improve=2.279095, (0 missing)
##       reimbursement2008 < 1775   to the left,  improve=2.187851, (0 missing)
##       copd              < 0.5    to the left,  improve=2.085109, (0 missing)
##   Surrogate splits:
##       kidney < 0.5    to the left,  agree=0.619, adj=0.071, (0 split)
##       copd   < 0.5    to the left,  agree=0.600, adj=0.027, (0 split)
##       age    < 38.5   to the right, agree=0.596, adj=0.016, (0 split)
## 
## Node number 210: 17 observations
##   predicted class=B2  expected loss=0.4705882  P(node) =0.00085
##     class counts:     4     9     4     0     0
##    probabilities: 0.235 0.529 0.235 0.000 0.000 
## 
## Node number 211: 14 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.0007
##     class counts:     5     2     6     1     0
##    probabilities: 0.357 0.143 0.429 0.071 0.000 
## 
## Node number 212: 55 observations
##   predicted class=B1  expected loss=0.3272727  P(node) =0.00275
##     class counts:    37    12     3     3     0
##    probabilities: 0.673 0.218 0.055 0.055 0.000 
## 
## Node number 213: 25 observations,    complexity param=0.000380286
##   predicted class=B2  expected loss=0.56  P(node) =0.00125
##     class counts:     9    11     2     3     0
##    probabilities: 0.360 0.440 0.080 0.120 0.000 
##   left son=426 (15 obs) right son=427 (10 obs)
##   Primary splits:
##       age               < 97.5   to the right, improve=1.6666670, (0 missing)
##       reimbursement2008 < 1995   to the right, improve=0.5153846, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1179487, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.1179487, (0 missing)
##       kidney            < 0.5    to the right, improve=0.1142857, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1685   to the right, agree=0.68, adj=0.2, (0 split)
## 
## Node number 214: 298 observations,    complexity param=0.001064801
##   predicted class=B1  expected loss=0.590604  P(node) =0.0149
##     class counts:   122   117    43    15     1
##    probabilities: 0.409 0.393 0.144 0.050 0.003 
##   left son=428 (162 obs) right son=429 (136 obs)
##   Primary splits:
##       age               < 71.5   to the left,  improve=3.1447400, (0 missing)
##       reimbursement2008 < 1760   to the left,  improve=2.8458740, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9979622, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7325015, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.4523398, (0 missing)
##   Surrogate splits:
##       stroke            < 0.5    to the left,  agree=0.550, adj=0.015, (0 split)
##       reimbursement2008 < 2495   to the left,  agree=0.550, adj=0.015, (0 split)
##       diabetes          < 0.5    to the right, agree=0.547, adj=0.007, (0 split)
## 
## Node number 215: 17 observations
##   predicted class=B2  expected loss=0.2941176  P(node) =0.00085
##     class counts:     2    12     2     1     0
##    probabilities: 0.118 0.706 0.118 0.059 0.000 
## 
## Node number 216: 281 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.4519573  P(node) =0.01405
##     class counts:   154    78    35    12     2
##    probabilities: 0.548 0.278 0.125 0.043 0.007 
##   left son=432 (68 obs) right son=433 (213 obs)
##   Primary splits:
##       age               < 67.5   to the left,  improve=1.4795500, (0 missing)
##       reimbursement2008 < 2995   to the right, improve=1.3998900, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.3998900, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.8817733, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6232495, (0 missing)
## 
## Node number 217: 36 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.3888889  P(node) =0.0018
##     class counts:     8    22     6     0     0
##    probabilities: 0.222 0.611 0.167 0.000 0.000 
##   left son=434 (10 obs) right son=435 (26 obs)
##   Primary splits:
##       reimbursement2008 < 2770   to the left,  improve=2.4239320, (0 missing)
##       age               < 77.5   to the left,  improve=1.1944440, (0 missing)
##       depression        < 0.5    to the left,  improve=1.0277780, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.9725830, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.9470085, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.778, adj=0.2, (0 split)
##       age        < 62.5   to the left,  agree=0.750, adj=0.1, (0 split)
## 
## Node number 218: 213 observations,    complexity param=0.000760572
##   predicted class=B1  expected loss=0.6103286  P(node) =0.01065
##     class counts:    83    75    33    22     0
##    probabilities: 0.390 0.352 0.155 0.103 0.000 
##   left son=436 (146 obs) right son=437 (67 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=2.4874440, (0 missing)
##       reimbursement2008 < 3335   to the right, improve=1.9134220, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.5529040, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.9344707, (0 missing)
##       copd              < 0.5    to the left,  improve=0.7994731, (0 missing)
##   Surrogate splits:
##       age < 35     to the right, agree=0.69, adj=0.015, (0 split)
## 
## Node number 219: 84 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.5119048  P(node) =0.0042
##     class counts:    20    41    20     3     0
##    probabilities: 0.238 0.488 0.238 0.036 0.000 
##   left son=438 (57 obs) right son=439 (27 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=1.5891120, (0 missing)
##       reimbursement2008 < 2735   to the right, improve=1.5503000, (0 missing)
##       age               < 70.5   to the right, improve=0.6885269, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.6357352, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4006211, (0 missing)
##   Surrogate splits:
##       age               < 91.5   to the left,  agree=0.726, adj=0.148, (0 split)
##       reimbursement2008 < 3415   to the left,  agree=0.702, adj=0.074, (0 split)
##       diabetes          < 0.5    to the right, agree=0.690, adj=0.037, (0 split)
## 
## Node number 220: 157 observations,    complexity param=0.0002788764
##   predicted class=B2  expected loss=0.5350318  P(node) =0.00785
##     class counts:    50    73    28     5     1
##    probabilities: 0.318 0.465 0.178 0.032 0.006 
##   left son=440 (150 obs) right son=441 (7 obs)
##   Primary splits:
##       stroke            < 0.5    to the left,  improve=1.886903, (0 missing)
##       copd              < 0.5    to the left,  improve=1.391085, (0 missing)
##       age               < 89.5   to the left,  improve=1.341972, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.236864, (0 missing)
##       reimbursement2008 < 2575   to the right, improve=1.066105, (0 missing)
## 
## Node number 221: 17 observations
##   predicted class=B3  expected loss=0.5294118  P(node) =0.00085
##     class counts:     4     4     8     1     0
##    probabilities: 0.235 0.235 0.471 0.059 0.000 
## 
## Node number 222: 81 observations,    complexity param=0.000190143
##   predicted class=B2  expected loss=0.4691358  P(node) =0.00405
##     class counts:    23    43     8     6     1
##    probabilities: 0.284 0.531 0.099 0.074 0.012 
##   left son=444 (70 obs) right son=445 (11 obs)
##   Primary splits:
##       reimbursement2008 < 3075   to the right, improve=1.2392180, (0 missing)
##       copd              < 0.5    to the left,  improve=1.1799880, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.9098037, (0 missing)
##       age               < 88.5   to the right, improve=0.6730540, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.3344166, (0 missing)
## 
## Node number 223: 31 observations
##   predicted class=B2  expected loss=0.1935484  P(node) =0.00155
##     class counts:     2    25     2     2     0
##    probabilities: 0.065 0.806 0.065 0.065 0.000 
## 
## Node number 224: 330 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.3787879  P(node) =0.0165
##     class counts:   205    77    36    10     2
##    probabilities: 0.621 0.233 0.109 0.030 0.006 
##   left son=448 (120 obs) right son=449 (210 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=3.020996, (0 missing)
##       reimbursement2008 < 7060   to the right, improve=2.104329, (0 missing)
##       age               < 59.5   to the right, improve=1.322458, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.319301, (0 missing)
##       copd              < 0.5    to the left,  improve=1.189474, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4060   to the left,  agree=0.652, adj=0.042, (0 split)
##       age               < 33.5   to the left,  agree=0.645, adj=0.025, (0 split)
## 
## Node number 225: 89 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.494382  P(node) =0.00445
##     class counts:    45    34     6     3     1
##    probabilities: 0.506 0.382 0.067 0.034 0.011 
##   left son=450 (15 obs) right son=451 (74 obs)
##   Primary splits:
##       reimbursement2008 < 12275  to the right, improve=3.3794110, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.9367485, (0 missing)
##       age               < 84.5   to the left,  improve=0.9235279, (0 missing)
##       ihd               < 0.5    to the right, improve=0.5528036, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5281343, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.921, adj=0.533, (0 split)
## 
## Node number 226: 58 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.4655172  P(node) =0.0029
##     class counts:    31    15     8     4     0
##    probabilities: 0.534 0.259 0.138 0.069 0.000 
##   left son=452 (27 obs) right son=453 (31 obs)
##   Primary splits:
##       reimbursement2008 < 6600   to the right, improve=2.6670370, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.9714330, (0 missing)
##       age               < 52.5   to the right, improve=1.1824140, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.9855451, (0 missing)
##       copd              < 0.5    to the right, improve=0.6557471, (0 missing)
##   Surrogate splits:
##       bucket2008    < 2.5    to the right, agree=0.948, adj=0.889, (0 split)
##       alzheimers    < 0.5    to the right, agree=0.655, adj=0.259, (0 split)
##       copd          < 0.5    to the right, agree=0.603, adj=0.148, (0 split)
##       heart.failure < 0.5    to the right, agree=0.603, adj=0.148, (0 split)
##       age           < 59     to the right, agree=0.586, adj=0.111, (0 split)
## 
## Node number 227: 86 observations,    complexity param=0.0003549336
##   predicted class=B2  expected loss=0.627907  P(node) =0.0043
##     class counts:    30    32    21     3     0
##    probabilities: 0.349 0.372 0.244 0.035 0.000 
##   left son=454 (14 obs) right son=455 (72 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=1.4390000, (0 missing)
##       copd              < 0.5    to the right, improve=1.2671440, (0 missing)
##       age               < 81.5   to the right, improve=1.2282230, (0 missing)
##       reimbursement2008 < 4375   to the left,  improve=0.9141660, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.6448968, (0 missing)
## 
## Node number 228: 42 observations,    complexity param=0.000760572
##   predicted class=B1  expected loss=0.5714286  P(node) =0.0021
##     class counts:    18    15     4     5     0
##    probabilities: 0.429 0.357 0.095 0.119 0.000 
##   left son=456 (10 obs) right son=457 (32 obs)
##   Primary splits:
##       reimbursement2008 < 3950   to the left,  improve=2.4148810, (0 missing)
##       copd              < 0.5    to the left,  improve=1.5594190, (0 missing)
##       age               < 64.5   to the left,  improve=1.4964990, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.1023810, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7069264, (0 missing)
## 
## Node number 229: 13 observations
##   predicted class=B3  expected loss=0.3846154  P(node) =0.00065
##     class counts:     3     0     8     2     0
##    probabilities: 0.231 0.000 0.615 0.154 0.000 
## 
## Node number 230: 41 observations
##   predicted class=B2  expected loss=0.4390244  P(node) =0.00205
##     class counts:     9    23     5     4     0
##    probabilities: 0.220 0.561 0.122 0.098 0.000 
## 
## Node number 231: 23 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.6086957  P(node) =0.00115
##     class counts:     6     6     9     2     0
##    probabilities: 0.261 0.261 0.391 0.087 0.000 
##   left son=462 (12 obs) right son=463 (11 obs)
##   Primary splits:
##       reimbursement2008 < 9740   to the right, improve=1.4920950, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.0489130, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.9011858, (0 missing)
##       age               < 82.5   to the right, improve=0.4774845, (0 missing)
##       kidney            < 0.5    to the right, improve=0.2572464, (0 missing)
##   Surrogate splits:
##       age        < 73.5   to the left,  agree=0.783, adj=0.545, (0 split)
##       bucket2008 < 2.5    to the right, agree=0.783, adj=0.545, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.652, adj=0.273, (0 split)
##       arthritis  < 0.5    to the left,  agree=0.652, adj=0.273, (0 split)
##       stroke     < 0.5    to the right, agree=0.565, adj=0.091, (0 split)
## 
## Node number 234: 136 observations,    complexity param=0.0006084576
##   predicted class=B2  expected loss=0.5147059  P(node) =0.0068
##     class counts:    40    66    23     7     0
##    probabilities: 0.294 0.485 0.169 0.051 0.000 
##   left son=468 (72 obs) right son=469 (64 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=2.205882, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=2.001349, (0 missing)
##       reimbursement2008 < 3710   to the left,  improve=1.407495, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.335690, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.307073, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 7755   to the left,  agree=0.574, adj=0.094, (0 split)
##       arthritis         < 0.5    to the right, agree=0.566, adj=0.078, (0 split)
##       bucket2008        < 3.5    to the left,  agree=0.559, adj=0.063, (0 split)
##       age               < 70.5   to the left,  agree=0.551, adj=0.047, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.551, adj=0.047, (0 split)
## 
## Node number 235: 57 observations,    complexity param=0.0006084576
##   predicted class=B1  expected loss=0.5789474  P(node) =0.00285
##     class counts:    24    15    13     5     0
##    probabilities: 0.421 0.263 0.228 0.088 0.000 
##   left son=470 (46 obs) right son=471 (11 obs)
##   Primary splits:
##       cancer            < 0.5    to the left,  improve=1.998405, (0 missing)
##       reimbursement2008 < 7955   to the right, improve=1.956558, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.956558, (0 missing)
##       age               < 91.5   to the right, improve=1.915288, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.477193, (0 missing)
## 
## Node number 238: 8 observations
##   predicted class=B2  expected loss=0.125  P(node) =0.0004
##     class counts:     0     7     0     1     0
##    probabilities: 0.000 0.875 0.000 0.125 0.000 
## 
## Node number 239: 86 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.5813953  P(node) =0.0043
##     class counts:    18    36    24     8     0
##    probabilities: 0.209 0.419 0.279 0.093 0.000 
##   left son=478 (79 obs) right son=479 (7 obs)
##   Primary splits:
##       reimbursement2008 < 15470  to the left,  improve=1.3701160, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.1865130, (0 missing)
##       age               < 75.5   to the left,  improve=0.7490688, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7421039, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.6663848, (0 missing)
## 
## Node number 240: 277 observations,    complexity param=0.0008746577
##   predicted class=B1  expected loss=0.5884477  P(node) =0.01385
##     class counts:   114    91    52    19     1
##    probabilities: 0.412 0.329 0.188 0.069 0.004 
##   left son=480 (199 obs) right son=481 (78 obs)
##   Primary splits:
##       reimbursement2008 < 8845   to the left,  improve=3.810926, (0 missing)
##       copd              < 0.5    to the left,  improve=3.392896, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=2.186722, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.961790, (0 missing)
##       age               < 65.5   to the right, improve=1.441728, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.953, adj=0.833, (0 split)
##       age        < 29.5   to the right, agree=0.722, adj=0.013, (0 split)
## 
## Node number 241: 514 observations,    complexity param=0.0008746577
##   predicted class=B2  expected loss=0.5583658  P(node) =0.0257
##     class counts:   178   227    77    29     3
##    probabilities: 0.346 0.442 0.150 0.056 0.006 
##   left son=482 (327 obs) right son=483 (187 obs)
##   Primary splits:
##       reimbursement2008 < 5045   to the right, improve=4.8841090, (0 missing)
##       age               < 77.5   to the left,  improve=3.3027050, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.9008760, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.9763248, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7270267, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.722, adj=0.235, (0 split)
## 
## Node number 242: 39 observations
##   predicted class=B2  expected loss=0.3076923  P(node) =0.00195
##     class counts:     4    27     6     1     1
##    probabilities: 0.103 0.692 0.154 0.026 0.026 
## 
## Node number 243: 134 observations,    complexity param=0.0005324004
##   predicted class=B2  expected loss=0.641791  P(node) =0.0067
##     class counts:    28    48    47    11     0
##    probabilities: 0.209 0.358 0.351 0.082 0.000 
##   left son=486 (120 obs) right son=487 (14 obs)
##   Primary splits:
##       age               < 55     to the right, improve=2.1647830, (0 missing)
##       reimbursement2008 < 6810   to the left,  improve=1.9339560, (0 missing)
##       depression        < 0.5    to the left,  improve=1.6866340, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.1492540, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.6824682, (0 missing)
## 
## Node number 246: 282 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5283688  P(node) =0.0141
##     class counts:    68   133    44    33     4
##    probabilities: 0.241 0.472 0.156 0.117 0.014 
##   left son=492 (183 obs) right son=493 (99 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=1.953103, (0 missing)
##       age               < 79.5   to the right, improve=1.706579, (0 missing)
##       copd              < 0.5    to the left,  improve=1.416467, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.155080, (0 missing)
##       reimbursement2008 < 3985   to the left,  improve=1.070900, (0 missing)
## 
## Node number 247: 253 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5454545  P(node) =0.01265
##     class counts:    46   115    69    21     2
##    probabilities: 0.182 0.455 0.273 0.083 0.008 
##   left son=494 (241 obs) right son=495 (12 obs)
##   Primary splits:
##       age               < 40.5   to the right, improve=1.7374600, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.3259550, (0 missing)
##       reimbursement2008 < 27370  to the left,  improve=1.2197450, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.9664812, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8621215, (0 missing)
## 
## Node number 248: 612 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.625817  P(node) =0.0306
##     class counts:   138   229   139    90    16
##    probabilities: 0.225 0.374 0.227 0.147 0.026 
##   left son=496 (346 obs) right son=497 (266 obs)
##   Primary splits:
##       reimbursement2008 < 6575   to the right, improve=1.895835, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.891624, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.621569, (0 missing)
##       age               < 79.5   to the right, improve=1.437351, (0 missing)
##       depression        < 0.5    to the left,  improve=1.158424, (0 missing)
##   Surrogate splits:
##       bucket2008    < 2.5    to the right, agree=0.884, adj=0.733, (0 split)
##       heart.failure < 0.5    to the right, agree=0.592, adj=0.060, (0 split)
##       ihd           < 0.5    to the right, agree=0.585, adj=0.045, (0 split)
##       age           < 97.5   to the left,  agree=0.574, adj=0.019, (0 split)
## 
## Node number 249: 26 observations,    complexity param=0.0001521144
##   predicted class=B3  expected loss=0.4230769  P(node) =0.0013
##     class counts:     1     7    15     3     0
##    probabilities: 0.038 0.269 0.577 0.115 0.000 
##   left son=498 (7 obs) right son=499 (19 obs)
##   Primary splits:
##       age               < 34     to the left,  improve=1.2272990, (0 missing)
##       reimbursement2008 < 9145   to the left,  improve=0.7893414, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.6847662, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.4615385, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.3738928, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 12030  to the right, agree=0.808, adj=0.286, (0 split)
## 
## Node number 250: 143 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.4055944  P(node) =0.00715
##     class counts:    20    85    22    15     1
##    probabilities: 0.140 0.594 0.154 0.105 0.007 
##   left son=500 (11 obs) right son=501 (132 obs)
##   Primary splits:
##       reimbursement2008 < 5155   to the right, improve=1.6981350, (0 missing)
##       age               < 81.5   to the right, improve=1.1198620, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.6517483, (0 missing)
##       cancer            < 0.5    to the right, improve=0.5239179, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5030303, (0 missing)
## 
## Node number 251: 309 observations,    complexity param=0.0002028192
##   predicted class=B2  expected loss=0.5404531  P(node) =0.01545
##     class counts:    36   142    85    40     6
##    probabilities: 0.117 0.460 0.275 0.129 0.019 
##   left son=502 (24 obs) right son=503 (285 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=1.6851900, (0 missing)
##       age               < 95.5   to the right, improve=1.5390930, (0 missing)
##       depression        < 0.5    to the right, improve=0.9172647, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8659759, (0 missing)
##       reimbursement2008 < 5385   to the right, improve=0.7334569, (0 missing)
## 
## Node number 252: 20 observations,    complexity param=0.0004563432
##   predicted class=B1  expected loss=0.45  P(node) =0.001
##     class counts:    11     5     1     3     0
##    probabilities: 0.550 0.250 0.050 0.150 0.000 
##   left son=504 (11 obs) right son=505 (9 obs)
##   Primary splits:
##       age               < 79.5   to the left,  improve=3.4121210, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.1890110, (0 missing)
##       reimbursement2008 < 40870  to the left,  improve=0.3978022, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1166667, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 41445  to the left,  agree=0.65, adj=0.222, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.60, adj=0.111, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.60, adj=0.111, (0 split)
## 
## Node number 253: 33 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6060606  P(node) =0.00165
##     class counts:     5    13     3    11     1
##    probabilities: 0.152 0.394 0.091 0.333 0.030 
##   left son=506 (20 obs) right son=507 (13 obs)
##   Primary splits:
##       age               < 79.5   to the left,  improve=3.605361, (0 missing)
##       arthritis         < 0.5    to the right, improve=2.541515, (0 missing)
##       cancer            < 0.5    to the right, improve=1.984848, (0 missing)
##       copd              < 0.5    to the right, improve=1.773737, (0 missing)
##       reimbursement2008 < 22825  to the left,  improve=1.341515, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 17295  to the right, agree=0.727, adj=0.308, (0 split)
##       bucket2008        < 3.5    to the right, agree=0.667, adj=0.154, (0 split)
##       heart.failure     < 0.5    to the right, agree=0.636, adj=0.077, (0 split)
## 
## Node number 254: 396 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6590909  P(node) =0.0198
##     class counts:    66   135    99    79    17
##    probabilities: 0.167 0.341 0.250 0.199 0.043 
##   left son=508 (233 obs) right son=509 (163 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=2.997912, (0 missing)
##       copd              < 0.5    to the left,  improve=1.877365, (0 missing)
##       age               < 49.5   to the right, improve=1.867161, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.727362, (0 missing)
##       reimbursement2008 < 23350  to the right, improve=1.426471, (0 missing)
##   Surrogate splits:
##       age               < 79.5   to the left,  agree=0.593, adj=0.012, (0 split)
##       reimbursement2008 < 15370  to the right, agree=0.593, adj=0.012, (0 split)
## 
## Node number 255: 487 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6201232  P(node) =0.02435
##     class counts:    37   185   104   136    25
##    probabilities: 0.076 0.380 0.214 0.279 0.051 
##   left son=510 (65 obs) right son=511 (422 obs)
##   Primary splits:
##       age               < 88.5   to the right, improve=4.7932710, (0 missing)
##       reimbursement2008 < 32590  to the left,  improve=2.4336710, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.5095490, (0 missing)
##       stroke            < 0.5    to the right, improve=1.4520590, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9634536, (0 missing)
## 
## Node number 320: 756 observations
##   predicted class=B1  expected loss=0.1216931  P(node) =0.0378
##     class counts:   664    57    27     7     1
##    probabilities: 0.878 0.075 0.036 0.009 0.001 
## 
## Node number 321: 830 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1626506  P(node) =0.0415
##     class counts:   695    80    41    12     2
##    probabilities: 0.837 0.096 0.049 0.014 0.002 
##   left son=642 (801 obs) right son=643 (29 obs)
##   Primary splits:
##       reimbursement2008 < 665    to the left,  improve=1.0300310, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4238073, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.4152878, (0 missing)
##       age               < 83.5   to the right, improve=0.3253936, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3055330, (0 missing)
## 
## Node number 322: 171 observations
##   predicted class=B1  expected loss=0.1812865  P(node) =0.00855
##     class counts:   140    21     7     3     0
##    probabilities: 0.819 0.123 0.041 0.018 0.000 
## 
## Node number 323: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     3     4     0     0     0
##    probabilities: 0.429 0.571 0.000 0.000 0.000 
## 
## Node number 352: 338 observations
##   predicted class=B1  expected loss=0.1745562  P(node) =0.0169
##     class counts:   279    29    20     8     2
##    probabilities: 0.825 0.086 0.059 0.024 0.006 
## 
## Node number 353: 206 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.223301  P(node) =0.0103
##     class counts:   160    31     6     9     0
##    probabilities: 0.777 0.150 0.029 0.044 0.000 
##   left son=706 (149 obs) right son=707 (57 obs)
##   Primary splits:
##       reimbursement2008 < 955    to the right, improve=2.3303040, (0 missing)
##       age               < 83.5   to the left,  improve=1.0927070, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.2820581, (0 missing)
##       depression        < 0.5    to the left,  improve=0.2779032, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2242064, (0 missing)
## 
## Node number 354: 182 observations
##   predicted class=B1  expected loss=0.2087912  P(node) =0.0091
##     class counts:   144    24     9     5     0
##    probabilities: 0.791 0.132 0.049 0.027 0.000 
## 
## Node number 355: 85 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3058824  P(node) =0.00425
##     class counts:    59    21     3     2     0
##    probabilities: 0.694 0.247 0.035 0.024 0.000 
##   left son=710 (76 obs) right son=711 (9 obs)
##   Primary splits:
##       reimbursement2008 < 785    to the left,  improve=1.6035430, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.6444788, (0 missing)
##       age               < 67.5   to the left,  improve=0.4285599, (0 missing)
##       kidney            < 0.5    to the right, improve=0.2709929, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2638534, (0 missing)
## 
## Node number 360: 449 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.2383073  P(node) =0.02245
##     class counts:   342    57    36    14     0
##    probabilities: 0.762 0.127 0.080 0.031 0.000 
##   left son=720 (283 obs) right son=721 (166 obs)
##   Primary splits:
##       reimbursement2008 < 1335   to the left,  improve=0.9925853, (0 missing)
##       age               < 86.5   to the right, improve=0.7150894, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.4184894, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.3114171, (0 missing)
##       copd              < 0.5    to the left,  improve=0.2866033, (0 missing)
##   Surrogate splits:
##       arthritis < 0.5    to the left,  agree=0.639, adj=0.024, (0 split)
##       cancer    < 0.5    to the left,  agree=0.635, adj=0.012, (0 split)
## 
## Node number 361: 137 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.3138686  P(node) =0.00685
##     class counts:    94    31     7     5     0
##    probabilities: 0.686 0.226 0.051 0.036 0.000 
##   left son=722 (50 obs) right son=723 (87 obs)
##   Primary splits:
##       reimbursement2008 < 1345   to the right, improve=0.88131890, (0 missing)
##       age               < 66.5   to the right, improve=0.69730870, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.63774780, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.09490691, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.05691905, (0 missing)
## 
## Node number 362: 143 observations,    complexity param=0.0001303838
##   predicted class=B1  expected loss=0.2937063  P(node) =0.00715
##     class counts:   101    28     8     4     2
##    probabilities: 0.706 0.196 0.056 0.028 0.014 
##   left son=724 (44 obs) right son=725 (99 obs)
##   Primary splits:
##       age               < 75.5   to the right, improve=1.3014760, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.1065060, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6625760, (0 missing)
##       reimbursement2008 < 1105   to the right, improve=0.6192812, (0 missing)
##       copd              < 0.5    to the right, improve=0.5462853, (0 missing)
## 
## Node number 363: 29 observations,    complexity param=0.0001303838
##   predicted class=B1  expected loss=0.5172414  P(node) =0.00145
##     class counts:    14    10     3     2     0
##    probabilities: 0.483 0.345 0.103 0.069 0.000 
##   left son=726 (17 obs) right son=727 (12 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=1.687965, (0 missing)
##       depression        < 0.5    to the right, improve=1.400383, (0 missing)
##       reimbursement2008 < 1230   to the right, improve=1.163009, (0 missing)
##       age               < 89.5   to the right, improve=1.116256, (0 missing)
##   Surrogate splits:
##       depression        < 0.5    to the left,  agree=0.690, adj=0.250, (0 split)
##       age               < 88     to the right, agree=0.655, adj=0.167, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.655, adj=0.167, (0 split)
##       arthritis         < 0.5    to the left,  agree=0.621, adj=0.083, (0 split)
##       reimbursement2008 < 1315   to the left,  agree=0.621, adj=0.083, (0 split)
## 
## Node number 368: 628 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.2563694  P(node) =0.0314
##     class counts:   467   104    43    12     2
##    probabilities: 0.744 0.166 0.068 0.019 0.003 
##   left son=736 (455 obs) right son=737 (173 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=1.5481310, (0 missing)
##       age               < 50     to the left,  improve=1.0731200, (0 missing)
##       reimbursement2008 < 1415   to the right, improve=0.7768717, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.6957436, (0 missing)
##       copd              < 0.5    to the right, improve=0.4845812, (0 missing)
##   Surrogate splits:
##       stroke < 0.5    to the left,  agree=0.726, adj=0.006, (0 split)
## 
## Node number 369: 63 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3650794  P(node) =0.00315
##     class counts:    40    15     7     1     0
##    probabilities: 0.635 0.238 0.111 0.016 0.000 
##   left son=738 (52 obs) right son=739 (11 obs)
##   Primary splits:
##       reimbursement2008 < 1485   to the right, improve=1.6751580, (0 missing)
##       age               < 77     to the left,  improve=1.2620310, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.8989344, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.8365607, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.4831933, (0 missing)
## 
## Node number 374: 35 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4857143  P(node) =0.00175
##     class counts:    18     9     5     3     0
##    probabilities: 0.514 0.257 0.143 0.086 0.000 
##   left son=748 (28 obs) right son=749 (7 obs)
##   Primary splits:
##       reimbursement2008 < 895    to the right, improve=1.2428570, (0 missing)
##       age               < 78.5   to the left,  improve=0.5571429, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1771429, (0 missing)
##       depression        < 0.5    to the right, improve=0.1771429, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.1695612, (0 missing)
##   Surrogate splits:
##       arthritis < 0.5    to the left,  agree=0.829, adj=0.143, (0 split)
## 
## Node number 375: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     1     5     2     0     0
##    probabilities: 0.125 0.625 0.250 0.000 0.000 
## 
## Node number 378: 310 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3193548  P(node) =0.0155
##     class counts:   211    65    24     9     1
##    probabilities: 0.681 0.210 0.077 0.029 0.003 
##   left son=756 (213 obs) right son=757 (97 obs)
##   Primary splits:
##       reimbursement2008 < 835    to the right, improve=1.2234200, (0 missing)
##       kidney            < 0.5    to the right, improve=0.9543067, (0 missing)
##       age               < 94.5   to the left,  improve=0.6199997, (0 missing)
##       copd              < 0.5    to the right, improve=0.5598660, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.3296654, (0 missing)
## 
## Node number 379: 12 observations
##   predicted class=B1  expected loss=0.6666667  P(node) =0.0006
##     class counts:     4     4     3     1     0
##    probabilities: 0.333 0.333 0.250 0.083 0.000 
## 
## Node number 380: 352 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4005682  P(node) =0.0176
##     class counts:   211    93    30    18     0
##    probabilities: 0.599 0.264 0.085 0.051 0.000 
##   left son=760 (242 obs) right son=761 (110 obs)
##   Primary splits:
##       depression    < 0.5    to the left,  improve=1.422004, (0 missing)
##       alzheimers    < 0.5    to the left,  improve=1.222427, (0 missing)
##       heart.failure < 0.5    to the left,  improve=1.193813, (0 missing)
##       kidney        < 0.5    to the left,  improve=1.141542, (0 missing)
##       age           < 41.5   to the left,  improve=1.015276, (0 missing)
##   Surrogate splits:
##       age < 31.5   to the right, agree=0.69, adj=0.009, (0 split)
## 
## Node number 381: 30 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4666667  P(node) =0.0015
##     class counts:    16     3     6     4     1
##    probabilities: 0.533 0.100 0.200 0.133 0.033 
##   left son=762 (22 obs) right son=763 (8 obs)
##   Primary splits:
##       age               < 70     to the right, improve=1.5590910, (0 missing)
##       reimbursement2008 < 1165   to the right, improve=0.3186603, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3000000, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.2421053, (0 missing)
##       depression        < 0.5    to the right, improve=0.1000000, (0 missing)
## 
## Node number 382: 7 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.00035
##     class counts:     5     1     1     0     0
##    probabilities: 0.714 0.143 0.143 0.000 0.000 
## 
## Node number 383: 18 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.0009
##     class counts:     3    10     3     2     0
##    probabilities: 0.167 0.556 0.167 0.111 0.000 
## 
## Node number 384: 395 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3012658  P(node) =0.01975
##     class counts:   276    70    39     9     1
##    probabilities: 0.699 0.177 0.099 0.023 0.003 
##   left son=768 (288 obs) right son=769 (107 obs)
##   Primary splits:
##       age               < 68.5   to the right, improve=1.6366860, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.9039390, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7765844, (0 missing)
##       reimbursement2008 < 2155   to the left,  improve=0.6564463, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5270843, (0 missing)
## 
## Node number 385: 122 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3934426  P(node) =0.0061
##     class counts:    74    30    11     7     0
##    probabilities: 0.607 0.246 0.090 0.057 0.000 
##   left son=770 (22 obs) right son=771 (100 obs)
##   Primary splits:
##       age               < 64     to the left,  improve=3.407899, (0 missing)
##       copd              < 0.5    to the left,  improve=2.182772, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.651095, (0 missing)
##       arthritis         < 0.5    to the right, improve=1.570224, (0 missing)
##       reimbursement2008 < 1715   to the left,  improve=1.522952, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2575   to the right, agree=0.828, adj=0.045, (0 split)
## 
## Node number 388: 45 observations
##   predicted class=B1  expected loss=0.2444444  P(node) =0.00225
##     class counts:    34     8     2     1     0
##    probabilities: 0.756 0.178 0.044 0.022 0.000 
## 
## Node number 389: 73 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.3972603  P(node) =0.00365
##     class counts:    44    23     4     1     1
##    probabilities: 0.603 0.315 0.055 0.014 0.014 
##   left son=778 (66 obs) right son=779 (7 obs)
##   Primary splits:
##       reimbursement2008 < 3390   to the left,  improve=1.0555650, (0 missing)
##       age               < 73.5   to the right, improve=0.9205119, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3975568, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.3383422, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.3014529, (0 missing)
## 
## Node number 390: 12 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0006
##     class counts:     8     3     0     1     0
##    probabilities: 0.667 0.250 0.000 0.083 0.000 
## 
## Node number 391: 26 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.3846154  P(node) =0.0013
##     class counts:     8    16     1     1     0
##    probabilities: 0.308 0.615 0.038 0.038 0.000 
##   left son=782 (7 obs) right son=783 (19 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=1.0289180, (0 missing)
##       age               < 71.5   to the left,  improve=0.9850816, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7134238, (0 missing)
##       reimbursement2008 < 2715   to the right, improve=0.6578089, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1266628, (0 missing)
##   Surrogate splits:
##       age < 83     to the right, agree=0.769, adj=0.143, (0 split)
## 
## Node number 394: 20 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.001
##     class counts:    15     3     0     2     0
##    probabilities: 0.750 0.150 0.000 0.100 0.000 
## 
## Node number 395: 58 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.5  P(node) =0.0029
##     class counts:    29    19     5     4     1
##    probabilities: 0.500 0.328 0.086 0.069 0.017 
##   left son=790 (50 obs) right son=791 (8 obs)
##   Primary splits:
##       reimbursement2008 < 2425   to the left,  improve=1.4217240, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.3465590, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.9017241, (0 missing)
##       age               < 71.5   to the right, improve=0.8647468, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.6097512, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.879, adj=0.125, (0 split)
## 
## Node number 396: 10 observations
##   predicted class=B1  expected loss=0.3  P(node) =0.0005
##     class counts:     7     0     3     0     0
##    probabilities: 0.700 0.000 0.300 0.000 0.000 
## 
## Node number 397: 130 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5461538  P(node) =0.0065
##     class counts:    59    43    24     3     1
##    probabilities: 0.454 0.331 0.185 0.023 0.008 
##   left son=794 (9 obs) right son=795 (121 obs)
##   Primary splits:
##       reimbursement2008 < 3265   to the right, improve=1.5391400, (0 missing)
##       age               < 79.5   to the left,  improve=1.1170220, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.0842510, (0 missing)
##       arthritis         < 0.5    to the right, improve=1.0803180, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.7807692, (0 missing)
##   Surrogate splits:
##       age < 48     to the left,  agree=0.938, adj=0.111, (0 split)
## 
## Node number 414: 12 observations
##   predicted class=B2  expected loss=0.4166667  P(node) =0.0006
##     class counts:     2     7     2     1     0
##    probabilities: 0.167 0.583 0.167 0.083 0.000 
## 
## Node number 415: 14 observations
##   predicted class=B3  expected loss=0.3571429  P(node) =0.0007
##     class counts:     1     3     9     1     0
##    probabilities: 0.071 0.214 0.643 0.071 0.000 
## 
## Node number 416: 307 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.3745928  P(node) =0.01535
##     class counts:   192    71    28    14     2
##    probabilities: 0.625 0.231 0.091 0.046 0.007 
##   left son=832 (163 obs) right son=833 (144 obs)
##   Primary splits:
##       diabetes          < 0.5    to the right, improve=1.8426850, (0 missing)
##       reimbursement2008 < 1595   to the right, improve=1.1555100, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.0463660, (0 missing)
##       cancer            < 0.5    to the right, improve=0.9571640, (0 missing)
##       age               < 88.5   to the left,  improve=0.9457736, (0 missing)
##   Surrogate splits:
##       age               < 75.5   to the right, agree=0.557, adj=0.056, (0 split)
##       reimbursement2008 < 1885   to the left,  agree=0.544, adj=0.028, (0 split)
## 
## Node number 417: 99 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.4747475  P(node) =0.00495
##     class counts:    52    34     7     5     1
##    probabilities: 0.525 0.343 0.071 0.051 0.010 
##   left son=834 (11 obs) right son=835 (88 obs)
##   Primary splits:
##       copd              < 0.5    to the right, improve=1.8888890, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.2998090, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.2183150, (0 missing)
##       reimbursement2008 < 2015   to the left,  improve=1.1747840, (0 missing)
##       age               < 88.5   to the left,  improve=0.8989783, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1615   to the left,  agree=0.909, adj=0.182, (0 split)
## 
## Node number 418: 261 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.4482759  P(node) =0.01305
##     class counts:   144    73    28    15     1
##    probabilities: 0.552 0.280 0.107 0.057 0.004 
##   left son=836 (228 obs) right son=837 (33 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=4.050652, (0 missing)
##       age               < 71.5   to the left,  improve=2.377089, (0 missing)
##       reimbursement2008 < 2485   to the left,  improve=1.974154, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.943678, (0 missing)
##       copd              < 0.5    to the left,  improve=1.910651, (0 missing)
## 
## Node number 419: 182 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.6098901  P(node) =0.0091
##     class counts:    71    68    29    11     3
##    probabilities: 0.390 0.374 0.159 0.060 0.016 
##   left son=838 (146 obs) right son=839 (36 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.1312160, (0 missing)
##       age               < 56.5   to the right, improve=2.0550500, (0 missing)
##       reimbursement2008 < 2235   to the left,  improve=1.8121880, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.1570780, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.5846992, (0 missing)
## 
## Node number 426: 15 observations
##   predicted class=B1  expected loss=0.5333333  P(node) =0.00075
##     class counts:     7     4     2     2     0
##    probabilities: 0.467 0.267 0.133 0.133 0.000 
## 
## Node number 427: 10 observations
##   predicted class=B2  expected loss=0.3  P(node) =0.0005
##     class counts:     2     7     0     1     0
##    probabilities: 0.200 0.700 0.000 0.100 0.000 
## 
## Node number 428: 162 observations,    complexity param=0.001064801
##   predicted class=B1  expected loss=0.5308642  P(node) =0.0081
##     class counts:    76    53    20    12     1
##    probabilities: 0.469 0.327 0.123 0.074 0.006 
##   left son=856 (76 obs) right son=857 (86 obs)
##   Primary splits:
##       reimbursement2008 < 1975   to the left,  improve=5.6805310, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.0157000, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8458215, (0 missing)
##       age               < 48.5   to the left,  improve=0.7356979, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.5696349, (0 missing)
##   Surrogate splits:
##       age          < 65.5   to the left,  agree=0.580, adj=0.105, (0 split)
##       osteoporosis < 0.5    to the right, agree=0.549, adj=0.039, (0 split)
##       diabetes     < 0.5    to the left,  agree=0.537, adj=0.013, (0 split)
##       stroke       < 0.5    to the right, agree=0.537, adj=0.013, (0 split)
## 
## Node number 429: 136 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.5294118  P(node) =0.0068
##     class counts:    46    64    23     3     0
##    probabilities: 0.338 0.471 0.169 0.022 0.000 
##   left son=858 (117 obs) right son=859 (19 obs)
##   Primary splits:
##       reimbursement2008 < 1705   to the right, improve=2.1418260, (0 missing)
##       age               < 77.5   to the right, improve=1.2623840, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7897266, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6677123, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.6652316, (0 missing)
## 
## Node number 432: 68 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.3529412  P(node) =0.0034
##     class counts:    44    18     3     3     0
##    probabilities: 0.647 0.265 0.044 0.044 0.000 
##   left son=864 (21 obs) right son=865 (47 obs)
##   Primary splits:
##       age               < 64.5   to the right, improve=2.2730500, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.3235290, (0 missing)
##       depression        < 0.5    to the left,  improve=1.1164500, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.9705882, (0 missing)
##       reimbursement2008 < 3195   to the left,  improve=0.9338624, (0 missing)
## 
## Node number 433: 213 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.4835681  P(node) =0.01065
##     class counts:   110    60    32     9     2
##    probabilities: 0.516 0.282 0.150 0.042 0.009 
##   left son=866 (92 obs) right son=867 (121 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=2.4788660, (0 missing)
##       reimbursement2008 < 3155   to the right, improve=1.9913470, (0 missing)
##       age               < 69.5   to the right, improve=1.9417030, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.1103130, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7492129, (0 missing)
##   Surrogate splits:
##       age               < 83.5   to the right, agree=0.577, adj=0.022, (0 split)
##       reimbursement2008 < 2535   to the left,  agree=0.573, adj=0.011, (0 split)
## 
## Node number 434: 10 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0005
##     class counts:     5     3     2     0     0
##    probabilities: 0.500 0.300 0.200 0.000 0.000 
## 
## Node number 435: 26 observations
##   predicted class=B2  expected loss=0.2692308  P(node) =0.0013
##     class counts:     3    19     4     0     0
##    probabilities: 0.115 0.731 0.154 0.000 0.000 
## 
## Node number 436: 146 observations,    complexity param=0.0006084576
##   predicted class=B1  expected loss=0.5547945  P(node) =0.0073
##     class counts:    65    52    16    13     0
##    probabilities: 0.445 0.356 0.110 0.089 0.000 
##   left son=872 (133 obs) right son=873 (13 obs)
##   Primary splits:
##       reimbursement2008 < 2585   to the right, improve=2.3843300, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.0271490, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.0118830, (0 missing)
##       depression        < 0.5    to the left,  improve=0.8908181, (0 missing)
##       age               < 74.5   to the left,  improve=0.8215784, (0 missing)
## 
## Node number 437: 67 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6567164  P(node) =0.00335
##     class counts:    18    23    17     9     0
##    probabilities: 0.269 0.343 0.254 0.134 0.000 
##   left son=874 (11 obs) right son=875 (56 obs)
##   Primary splits:
##       reimbursement2008 < 2605   to the left,  improve=0.8274375, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8104509, (0 missing)
##       age               < 58.5   to the left,  improve=0.7605544, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5110835, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=0.2925650, (0 missing)
##   Surrogate splits:
##       age < 47.5   to the left,  agree=0.881, adj=0.273, (0 split)
## 
## Node number 438: 57 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.4912281  P(node) =0.00285
##     class counts:    16    29     9     3     0
##    probabilities: 0.281 0.509 0.158 0.053 0.000 
##   left son=876 (41 obs) right son=877 (16 obs)
##   Primary splits:
##       reimbursement2008 < 2735   to the right, improve=2.1723900, (0 missing)
##       age               < 70.5   to the left,  improve=1.5686010, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.1967800, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6143996, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=0.4557416, (0 missing)
## 
## Node number 439: 27 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.5555556  P(node) =0.00135
##     class counts:     4    12    11     0     0
##    probabilities: 0.148 0.444 0.407 0.000 0.000 
##   left son=878 (9 obs) right son=879 (18 obs)
##   Primary splits:
##       age               < 84.5   to the right, improve=1.92592600, (0 missing)
##       reimbursement2008 < 3145   to the right, improve=0.29259260, (0 missing)
##       depression        < 0.5    to the left,  improve=0.29259260, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.20797720, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.07494553, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2695   to the left,  agree=0.741, adj=0.222, (0 split)
## 
## Node number 440: 150 observations,    complexity param=0.0002788764
##   predicted class=B2  expected loss=0.5533333  P(node) =0.0075
##     class counts:    50    67    27     5     1
##    probabilities: 0.333 0.447 0.180 0.033 0.007 
##   left son=880 (142 obs) right son=881 (8 obs)
##   Primary splits:
##       age               < 89.5   to the left,  improve=1.4895310, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.4218900, (0 missing)
##       reimbursement2008 < 2825   to the right, improve=1.3233330, (0 missing)
##       copd              < 0.5    to the left,  improve=1.2090920, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.9791534, (0 missing)
## 
## Node number 441: 7 observations
##   predicted class=B2  expected loss=0.1428571  P(node) =0.00035
##     class counts:     0     6     1     0     0
##    probabilities: 0.000 0.857 0.143 0.000 0.000 
## 
## Node number 444: 70 observations,    complexity param=0.000190143
##   predicted class=B2  expected loss=0.5  P(node) =0.0035
##     class counts:    22    35     8     4     1
##    probabilities: 0.314 0.500 0.114 0.057 0.014 
##   left son=888 (40 obs) right son=889 (30 obs)
##   Primary splits:
##       reimbursement2008 < 3265   to the left,  improve=2.1952380, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8206310, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.8196825, (0 missing)
##       copd              < 0.5    to the left,  improve=0.7659533, (0 missing)
##       age               < 82.5   to the right, improve=0.6993816, (0 missing)
##   Surrogate splits:
##       age           < 54.5   to the right, agree=0.614, adj=0.100, (0 split)
##       cancer        < 0.5    to the left,  agree=0.614, adj=0.100, (0 split)
##       heart.failure < 0.5    to the right, agree=0.614, adj=0.100, (0 split)
##       depression    < 0.5    to the right, agree=0.600, adj=0.067, (0 split)
## 
## Node number 445: 11 observations
##   predicted class=B2  expected loss=0.2727273  P(node) =0.00055
##     class counts:     1     8     0     2     0
##    probabilities: 0.091 0.727 0.000 0.182 0.000 
## 
## Node number 448: 120 observations,    complexity param=0.0001014096
##   predicted class=B1  expected loss=0.275  P(node) =0.006
##     class counts:    87    21     8     4     0
##    probabilities: 0.725 0.175 0.067 0.033 0.000 
##   left son=896 (26 obs) right son=897 (94 obs)
##   Primary splits:
##       reimbursement2008 < 8195   to the right, improve=1.9843150, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.6375210, (0 missing)
##       age               < 49.5   to the right, improve=1.1599100, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.1550330, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5544872, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.975, adj=0.885, (0 split)
## 
## Node number 449: 210 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.4380952  P(node) =0.0105
##     class counts:   118    56    28     6     2
##    probabilities: 0.562 0.267 0.133 0.029 0.010 
##   left son=898 (89 obs) right son=899 (121 obs)
##   Primary splits:
##       reimbursement2008 < 7060   to the right, improve=1.5649970, (0 missing)
##       age               < 59.5   to the right, improve=0.9328321, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.8837035, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.5471253, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4479437, (0 missing)
##   Surrogate splits:
##       bucket2008    < 2.5    to the right, agree=0.952, adj=0.888, (0 split)
##       kidney        < 0.5    to the right, agree=0.662, adj=0.202, (0 split)
##       age           < 83.5   to the right, agree=0.619, adj=0.101, (0 split)
##       heart.failure < 0.5    to the right, agree=0.619, adj=0.101, (0 split)
##       copd          < 0.5    to the right, agree=0.614, adj=0.090, (0 split)
## 
## Node number 450: 15 observations
##   predicted class=B1  expected loss=0.2  P(node) =0.00075
##     class counts:    12     1     1     1     0
##    probabilities: 0.800 0.067 0.067 0.067 0.000 
## 
## Node number 451: 74 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.5540541  P(node) =0.0037
##     class counts:    33    33     5     2     1
##    probabilities: 0.446 0.446 0.068 0.027 0.014 
##   left son=902 (60 obs) right son=903 (14 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.3193050, (0 missing)
##       age               < 66.5   to the left,  improve=1.1497330, (0 missing)
##       reimbursement2008 < 6655   to the left,  improve=0.9978265, (0 missing)
##       ihd               < 0.5    to the right, improve=0.5988288, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4239269, (0 missing)
##   Surrogate splits:
##       age               < 90.5   to the left,  agree=0.851, adj=0.214, (0 split)
##       reimbursement2008 < 11700  to the left,  agree=0.838, adj=0.143, (0 split)
## 
## Node number 452: 27 observations
##   predicted class=B1  expected loss=0.2962963  P(node) =0.00135
##     class counts:    19     4     1     3     0
##    probabilities: 0.704 0.148 0.037 0.111 0.000 
## 
## Node number 453: 31 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.6129032  P(node) =0.00155
##     class counts:    12    11     7     1     0
##    probabilities: 0.387 0.355 0.226 0.032 0.000 
##   left son=906 (16 obs) right son=907 (15 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the right, improve=0.9637097, (0 missing)
##       copd              < 0.5    to the right, improve=0.9101382, (0 missing)
##       reimbursement2008 < 4635   to the right, improve=0.7294660, (0 missing)
##       ihd               < 0.5    to the right, improve=0.6841642, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5193819, (0 missing)
##   Surrogate splits:
##       kidney            < 0.5    to the right, agree=0.710, adj=0.400, (0 split)
##       reimbursement2008 < 5195   to the right, agree=0.677, adj=0.333, (0 split)
##       age               < 68     to the right, agree=0.613, adj=0.200, (0 split)
##       ihd               < 0.5    to the right, agree=0.613, adj=0.200, (0 split)
##       copd              < 0.5    to the right, agree=0.581, adj=0.133, (0 split)
## 
## Node number 454: 14 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.0007
##     class counts:     8     3     2     1     0
##    probabilities: 0.571 0.214 0.143 0.071 0.000 
## 
## Node number 455: 72 observations,    complexity param=0.0003549336
##   predicted class=B2  expected loss=0.5972222  P(node) =0.0036
##     class counts:    22    29    19     2     0
##    probabilities: 0.306 0.403 0.264 0.028 0.000 
##   left son=910 (18 obs) right son=911 (54 obs)
##   Primary splits:
##       reimbursement2008 < 4780   to the left,  improve=1.4537040, (0 missing)
##       copd              < 0.5    to the right, improve=1.3585470, (0 missing)
##       age               < 80.5   to the right, improve=0.9255324, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.7387668, (0 missing)
##       kidney            < 0.5    to the right, improve=0.4950505, (0 missing)
## 
## Node number 456: 10 observations
##   predicted class=B2  expected loss=0.3  P(node) =0.0005
##     class counts:     2     7     1     0     0
##    probabilities: 0.200 0.700 0.100 0.000 0.000 
## 
## Node number 457: 32 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5  P(node) =0.0016
##     class counts:    16     8     3     5     0
##    probabilities: 0.500 0.250 0.094 0.156 0.000 
##   left son=914 (25 obs) right son=915 (7 obs)
##   Primary splits:
##       age               < 64.5   to the right, improve=1.3717860, (0 missing)
##       copd              < 0.5    to the left,  improve=1.3541670, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.8125000, (0 missing)
##       reimbursement2008 < 5140   to the left,  improve=0.5882937, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.2860714, (0 missing)
##   Surrogate splits:
##       arthritis < 0.5    to the left,  agree=0.812, adj=0.143, (0 split)
## 
## Node number 462: 12 observations
##   predicted class=B1  expected loss=0.5833333  P(node) =0.0006
##     class counts:     5     2     3     2     0
##    probabilities: 0.417 0.167 0.250 0.167 0.000 
## 
## Node number 463: 11 observations
##   predicted class=B3  expected loss=0.4545455  P(node) =0.00055
##     class counts:     1     4     6     0     0
##    probabilities: 0.091 0.364 0.545 0.000 0.000 
## 
## Node number 468: 72 observations,    complexity param=0.0006084576
##   predicted class=B2  expected loss=0.5277778  P(node) =0.0036
##     class counts:    28    34     7     3     0
##    probabilities: 0.389 0.472 0.097 0.042 0.000 
##   left son=936 (27 obs) right son=937 (45 obs)
##   Primary splits:
##       reimbursement2008 < 7260   to the right, improve=3.153704, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.757692, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.512060, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.494255, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.126923, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.903, adj=0.741, (0 split)
##       age        < 57.5   to the left,  agree=0.639, adj=0.037, (0 split)
##       kidney     < 0.5    to the right, agree=0.639, adj=0.037, (0 split)
## 
## Node number 469: 64 observations,    complexity param=0.0003549336
##   predicted class=B2  expected loss=0.5  P(node) =0.0032
##     class counts:    12    32    16     4     0
##    probabilities: 0.188 0.500 0.250 0.062 0.000 
##   left son=938 (12 obs) right son=939 (52 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=2.2692310, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.4314290, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.7790989, (0 missing)
##       reimbursement2008 < 23405  to the right, improve=0.7180451, (0 missing)
##       age               < 76.5   to the left,  improve=0.6937984, (0 missing)
## 
## Node number 470: 46 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.5217391  P(node) =0.0023
##     class counts:    22     9    10     5     0
##    probabilities: 0.478 0.196 0.217 0.109 0.000 
##   left son=940 (13 obs) right son=941 (33 obs)
##   Primary splits:
##       age               < 91.5   to the right, improve=2.1375290, (0 missing)
##       reimbursement2008 < 13835  to the left,  improve=1.6227110, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.1379310, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.9519520, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.6946237, (0 missing)
## 
## Node number 471: 11 observations
##   predicted class=B2  expected loss=0.4545455  P(node) =0.00055
##     class counts:     2     6     3     0     0
##    probabilities: 0.182 0.545 0.273 0.000 0.000 
## 
## Node number 478: 79 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.556962  P(node) =0.00395
##     class counts:    15    35    23     6     0
##    probabilities: 0.190 0.443 0.291 0.076 0.000 
##   left son=956 (41 obs) right son=957 (38 obs)
##   Primary splits:
##       age               < 75.5   to the left,  improve=0.9917453, (0 missing)
##       reimbursement2008 < 4785   to the left,  improve=0.9835014, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.7155960, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.6911068, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6784535, (0 missing)
##   Surrogate splits:
##       arthritis         < 0.5    to the left,  agree=0.658, adj=0.289, (0 split)
##       reimbursement2008 < 8635   to the left,  agree=0.633, adj=0.237, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.608, adj=0.184, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.582, adj=0.132, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.557, adj=0.079, (0 split)
## 
## Node number 479: 7 observations
##   predicted class=B1  expected loss=0.5714286  P(node) =0.00035
##     class counts:     3     1     1     2     0
##    probabilities: 0.429 0.143 0.143 0.286 0.000 
## 
## Node number 480: 199 observations,    complexity param=0.0008746577
##   predicted class=B1  expected loss=0.5477387  P(node) =0.00995
##     class counts:    90    72    32     5     0
##    probabilities: 0.452 0.362 0.161 0.025 0.000 
##   left son=960 (155 obs) right son=961 (44 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=4.0942290, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.4154020, (0 missing)
##       reimbursement2008 < 7230   to the right, improve=1.3220170, (0 missing)
##       age               < 62.5   to the right, improve=0.9109503, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.7457594, (0 missing)
##   Surrogate splits:
##       age < 31.5   to the right, agree=0.789, adj=0.045, (0 split)
## 
## Node number 481: 78 observations,    complexity param=0.000507048
##   predicted class=B1  expected loss=0.6923077  P(node) =0.0039
##     class counts:    24    19    20    14     1
##    probabilities: 0.308 0.244 0.256 0.179 0.013 
##   left son=962 (52 obs) right son=963 (26 obs)
##   Primary splits:
##       reimbursement2008 < 11475  to the right, improve=1.756410, (0 missing)
##       age               < 65.5   to the right, improve=1.591079, (0 missing)
##       depression        < 0.5    to the left,  improve=1.545455, (0 missing)
##       copd              < 0.5    to the left,  improve=1.292572, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.277778, (0 missing)
##   Surrogate splits:
##       ihd < 0.5    to the right, agree=0.705, adj=0.115, (0 split)
##       age < 49.5   to the right, agree=0.679, adj=0.038, (0 split)
## 
## Node number 482: 327 observations,    complexity param=0.0008746577
##   predicted class=B1  expected loss=0.6116208  P(node) =0.01635
##     class counts:   127   125    50    22     3
##    probabilities: 0.388 0.382 0.153 0.067 0.009 
##   left son=964 (170 obs) right son=965 (157 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=2.493752, (0 missing)
##       reimbursement2008 < 5355   to the left,  improve=2.213439, (0 missing)
##       age               < 97.5   to the left,  improve=2.016707, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.460516, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.183698, (0 missing)
##   Surrogate splits:
##       alzheimers        < 0.5    to the left,  agree=0.584, adj=0.134, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.572, adj=0.108, (0 split)
##       reimbursement2008 < 9565   to the left,  agree=0.566, adj=0.096, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.557, adj=0.076, (0 split)
##       age               < 80.5   to the left,  agree=0.554, adj=0.070, (0 split)
## 
## Node number 483: 187 observations,    complexity param=0.000380286
##   predicted class=B2  expected loss=0.4545455  P(node) =0.00935
##     class counts:    51   102    27     7     0
##    probabilities: 0.273 0.545 0.144 0.037 0.000 
##   left son=966 (74 obs) right son=967 (113 obs)
##   Primary splits:
##       age               < 77.5   to the left,  improve=1.8473350, (0 missing)
##       reimbursement2008 < 4720   to the left,  improve=1.8297120, (0 missing)
##       stroke            < 0.5    to the right, improve=0.8760224, (0 missing)
##       depression        < 0.5    to the right, improve=0.8148550, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.6872708, (0 missing)
## 
## Node number 486: 120 observations,    complexity param=0.0005324004
##   predicted class=B2  expected loss=0.6166667  P(node) =0.006
##     class counts:    25    46    38    11     0
##    probabilities: 0.208 0.383 0.317 0.092 0.000 
##   left son=972 (8 obs) right son=973 (112 obs)
##   Primary splits:
##       age               < 59.5   to the left,  improve=3.0630950, (0 missing)
##       reimbursement2008 < 6810   to the left,  improve=2.3493340, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.5126620, (0 missing)
##       depression        < 0.5    to the left,  improve=1.2818450, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.9859477, (0 missing)
## 
## Node number 487: 14 observations
##   predicted class=B3  expected loss=0.3571429  P(node) =0.0007
##     class counts:     3     2     9     0     0
##    probabilities: 0.214 0.143 0.643 0.000 0.000 
## 
## Node number 492: 183 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.557377  P(node) =0.00915
##     class counts:    52    81    23    23     4
##    probabilities: 0.284 0.443 0.126 0.126 0.022 
##   left son=984 (56 obs) right son=985 (127 obs)
##   Primary splits:
##       reimbursement2008 < 11200  to the right, improve=1.3922150, (0 missing)
##       age               < 67.5   to the right, improve=1.3360660, (0 missing)
##       copd              < 0.5    to the left,  improve=1.2442960, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.9452905, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9450073, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.907, adj=0.696, (0 split)
## 
## Node number 493: 99 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4747475  P(node) =0.00495
##     class counts:    16    52    21    10     0
##    probabilities: 0.162 0.525 0.212 0.101 0.000 
##   left son=986 (37 obs) right son=987 (62 obs)
##   Primary splits:
##       age               < 79.5   to the right, improve=2.3556310, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.3800430, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.2000000, (0 missing)
##       reimbursement2008 < 25605  to the right, improve=1.1394690, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9554113, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 13065  to the right, agree=0.657, adj=0.081, (0 split)
## 
## Node number 494: 241 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5435685  P(node) =0.01205
##     class counts:    46   110    62    21     2
##    probabilities: 0.191 0.456 0.257 0.087 0.008 
##   left son=988 (16 obs) right son=989 (225 obs)
##   Primary splits:
##       age               < 54.5   to the left,  improve=1.3463230, (0 missing)
##       reimbursement2008 < 4070   to the right, improve=1.3125650, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.3020150, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.0773410, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6861288, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 52960  to the right, agree=0.938, adj=0.062, (0 split)
##       bucket2008        < 4.5    to the right, agree=0.938, adj=0.062, (0 split)
## 
## Node number 495: 12 observations
##   predicted class=B3  expected loss=0.4166667  P(node) =0.0006
##     class counts:     0     5     7     0     0
##    probabilities: 0.000 0.417 0.583 0.000 0.000 
## 
## Node number 496: 346 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6531792  P(node) =0.0173
##     class counts:    88   120    71    57    10
##    probabilities: 0.254 0.347 0.205 0.165 0.029 
##   left son=992 (67 obs) right son=993 (279 obs)
##   Primary splits:
##       age               < 85.5   to the right, improve=2.853034, (0 missing)
##       reimbursement2008 < 6780   to the left,  improve=2.493960, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.888712, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.770580, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.127732, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 15040  to the right, agree=0.812, adj=0.03, (0 split)
## 
## Node number 497: 266 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.5902256  P(node) =0.0133
##     class counts:    50   109    68    33     6
##    probabilities: 0.188 0.410 0.256 0.124 0.023 
##   left son=994 (19 obs) right son=995 (247 obs)
##   Primary splits:
##       age               < 92.5   to the right, improve=3.1654140, (0 missing)
##       reimbursement2008 < 6185   to the left,  improve=2.8527200, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.0112500, (0 missing)
##       ihd               < 0.5    to the right, improve=0.9988659, (0 missing)
##       depression        < 0.5    to the right, improve=0.8363985, (0 missing)
## 
## Node number 498: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     0     4     3     0     0
##    probabilities: 0.000 0.571 0.429 0.000 0.000 
## 
## Node number 499: 19 observations
##   predicted class=B3  expected loss=0.3684211  P(node) =0.00095
##     class counts:     1     3    12     3     0
##    probabilities: 0.053 0.158 0.632 0.158 0.000 
## 
## Node number 500: 11 observations
##   predicted class=B2  expected loss=0.09090909  P(node) =0.00055
##     class counts:     0    10     0     1     0
##    probabilities: 0.000 0.909 0.000 0.091 0.000 
## 
## Node number 501: 132 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.4318182  P(node) =0.0066
##     class counts:    20    75    22    14     1
##    probabilities: 0.152 0.568 0.167 0.106 0.008 
##   left son=1002 (107 obs) right son=1003 (25 obs)
##   Primary splits:
##       reimbursement2008 < 4815   to the left,  improve=1.3622030, (0 missing)
##       age               < 80.5   to the right, improve=1.1112760, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7506887, (0 missing)
##       copd              < 0.5    to the right, improve=0.7453568, (0 missing)
##       cancer            < 0.5    to the right, improve=0.5247008, (0 missing)
## 
## Node number 502: 24 observations,    complexity param=0.0002028192
##   predicted class=B3  expected loss=0.6666667  P(node) =0.0012
##     class counts:     7     7     8     2     0
##    probabilities: 0.292 0.292 0.333 0.083 0.000 
##   left son=1004 (16 obs) right son=1005 (8 obs)
##   Primary splits:
##       age               < 70     to the right, improve=1.458333, (0 missing)
##       reimbursement2008 < 7185   to the right, improve=1.305556, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.261111, (0 missing)
##       depression        < 0.5    to the right, improve=1.083333, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.083333, (0 missing)
## 
## Node number 503: 285 observations,    complexity param=0.0002028192
##   predicted class=B2  expected loss=0.5263158  P(node) =0.01425
##     class counts:    29   135    77    38     6
##    probabilities: 0.102 0.474 0.270 0.133 0.021 
##   left son=1006 (253 obs) right son=1007 (32 obs)
##   Primary splits:
##       reimbursement2008 < 5725   to the right, improve=1.2734940, (0 missing)
##       age               < 95.5   to the right, improve=1.2461000, (0 missing)
##       copd              < 0.5    to the left,  improve=1.1568740, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.6666667, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.6302632, (0 missing)
## 
## Node number 504: 11 observations
##   predicted class=B1  expected loss=0.1818182  P(node) =0.00055
##     class counts:     9     0     1     1     0
##    probabilities: 0.818 0.000 0.091 0.091 0.000 
## 
## Node number 505: 9 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.00045
##     class counts:     2     5     0     2     0
##    probabilities: 0.222 0.556 0.000 0.222 0.000 
## 
## Node number 506: 20 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.4  P(node) =0.001
##     class counts:     1    12     2     4     1
##    probabilities: 0.050 0.600 0.100 0.200 0.050 
##   left son=1012 (13 obs) right son=1013 (7 obs)
##   Primary splits:
##       reimbursement2008 < 22825  to the left,  improve=4.1615380, (0 missing)
##       copd              < 0.5    to the right, improve=1.2757580, (0 missing)
##       age               < 68.5   to the right, improve=0.2833333, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.1000000, (0 missing)
##   Surrogate splits:
##       age          < 72.5   to the left,  agree=0.75, adj=0.286, (0 split)
##       osteoporosis < 0.5    to the left,  agree=0.75, adj=0.286, (0 split)
## 
## Node number 507: 13 observations
##   predicted class=B4  expected loss=0.4615385  P(node) =0.00065
##     class counts:     4     1     1     7     0
##    probabilities: 0.308 0.077 0.077 0.538 0.000 
## 
## Node number 508: 233 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6866953  P(node) =0.01165
##     class counts:    48    73    49    55     8
##    probabilities: 0.206 0.313 0.210 0.236 0.034 
##   left son=1016 (95 obs) right son=1017 (138 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.100995, (0 missing)
##       reimbursement2008 < 25650  to the right, improve=1.969720, (0 missing)
##       age               < 89.5   to the right, improve=1.419602, (0 missing)
##       stroke            < 0.5    to the right, improve=1.223362, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.077810, (0 missing)
##   Surrogate splits:
##       heart.failure < 0.5    to the left,  agree=0.609, adj=0.042, (0 split)
##       age           < 53.5   to the left,  agree=0.601, adj=0.021, (0 split)
## 
## Node number 509: 163 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6196319  P(node) =0.00815
##     class counts:    18    62    50    24     9
##    probabilities: 0.110 0.380 0.307 0.147 0.055 
##   left son=1018 (140 obs) right son=1019 (23 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the right, improve=2.091784, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.893817, (0 missing)
##       age               < 65     to the right, improve=1.795615, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.116333, (0 missing)
##       reimbursement2008 < 16525  to the right, improve=1.100480, (0 missing)
## 
## Node number 510: 65 observations
##   predicted class=B2  expected loss=0.4307692  P(node) =0.00325
##     class counts:     7    37     7    10     4
##    probabilities: 0.108 0.569 0.108 0.154 0.062 
## 
## Node number 511: 422 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6492891  P(node) =0.0211
##     class counts:    30   148    97   126    21
##    probabilities: 0.071 0.351 0.230 0.299 0.050 
##   left son=1022 (91 obs) right son=1023 (331 obs)
##   Primary splits:
##       reimbursement2008 < 32040  to the left,  improve=2.8304840, (0 missing)
##       stroke            < 0.5    to the right, improve=2.0316160, (0 missing)
##       age               < 34.5   to the left,  improve=1.6984130, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9304072, (0 missing)
##       bucket2008        < 4.5    to the right, improve=0.8586131, (0 missing)
## 
## Node number 642: 801 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1585518  P(node) =0.04005
##     class counts:   674    73    40    12     2
##    probabilities: 0.841 0.091 0.050 0.015 0.002 
##   left son=1284 (94 obs) right son=1285 (707 obs)
##   Primary splits:
##       reimbursement2008 < 245    to the left,  improve=0.4516579, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.3483743, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.3415246, (0 missing)
##       age               < 83.5   to the right, improve=0.3232539, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.2952273, (0 missing)
## 
## Node number 643: 29 observations
##   predicted class=B1  expected loss=0.2758621  P(node) =0.00145
##     class counts:    21     7     1     0     0
##    probabilities: 0.724 0.241 0.034 0.000 0.000 
## 
## Node number 706: 149 observations
##   predicted class=B1  expected loss=0.1677852  P(node) =0.00745
##     class counts:   124    18     3     4     0
##    probabilities: 0.832 0.121 0.020 0.027 0.000 
## 
## Node number 707: 57 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3684211  P(node) =0.00285
##     class counts:    36    13     3     5     0
##    probabilities: 0.632 0.228 0.053 0.088 0.000 
##   left son=1414 (43 obs) right son=1415 (14 obs)
##   Primary splits:
##       age               < 83.5   to the left,  improve=2.8778340, (0 missing)
##       reimbursement2008 < 945    to the left,  improve=1.6818210, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7156433, (0 missing)
## 
## Node number 710: 76 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2763158  P(node) =0.0038
##     class counts:    55    16     3     2     0
##    probabilities: 0.724 0.211 0.039 0.026 0.000 
##   left son=1420 (9 obs) right son=1421 (67 obs)
##   Primary splits:
##       age               < 81     to the right, improve=0.8204155, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5009717, (0 missing)
##       kidney            < 0.5    to the right, improve=0.4025050, (0 missing)
##       reimbursement2008 < 775    to the left,  improve=0.2718808, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2404084, (0 missing)
## 
## Node number 711: 9 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.00045
##     class counts:     4     5     0     0     0
##    probabilities: 0.444 0.556 0.000 0.000 0.000 
## 
## Node number 720: 283 observations,    complexity param=5.07048e-05
##   predicted class=B1  expected loss=0.2120141  P(node) =0.01415
##     class counts:   223    29    22     9     0
##    probabilities: 0.788 0.102 0.078 0.032 0.000 
##   left son=1440 (27 obs) right son=1441 (256 obs)
##   Primary splits:
##       age               < 87.5   to the right, improve=0.7753638, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.5910595, (0 missing)
##       reimbursement2008 < 1315   to the right, improve=0.5333621, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4097368, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.3159337, (0 missing)
## 
## Node number 721: 166 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.2831325  P(node) =0.0083
##     class counts:   119    28    14     5     0
##    probabilities: 0.717 0.169 0.084 0.030 0.000 
##   left son=1442 (158 obs) right son=1443 (8 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=0.7746302, (0 missing)
##       age               < 73.5   to the right, improve=0.7080149, (0 missing)
##       reimbursement2008 < 1525   to the right, improve=0.3417250, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3081519, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.2090240, (0 missing)
## 
## Node number 722: 50 observations
##   predicted class=B1  expected loss=0.26  P(node) =0.0025
##     class counts:    37     7     4     2     0
##    probabilities: 0.740 0.140 0.080 0.040 0.000 
## 
## Node number 723: 87 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.3448276  P(node) =0.00435
##     class counts:    57    24     3     3     0
##    probabilities: 0.655 0.276 0.034 0.034 0.000 
##   left son=1446 (52 obs) right son=1447 (35 obs)
##   Primary splits:
##       reimbursement2008 < 1235   to the left,  improve=1.3847290, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.0449780, (0 missing)
##       age               < 56.5   to the left,  improve=0.4942529, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.3668719, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.2869269, (0 missing)
##   Surrogate splits:
##       age        < 66.5   to the left,  agree=0.621, adj=0.057, (0 split)
##       depression < 0.5    to the left,  agree=0.609, adj=0.029, (0 split)
## 
## Node number 724: 44 observations
##   predicted class=B1  expected loss=0.1818182  P(node) =0.0022
##     class counts:    36     5     1     1     1
##    probabilities: 0.818 0.114 0.023 0.023 0.023 
## 
## Node number 725: 99 observations,    complexity param=0.0001303838
##   predicted class=B1  expected loss=0.3434343  P(node) =0.00495
##     class counts:    65    23     7     3     1
##    probabilities: 0.657 0.232 0.071 0.030 0.010 
##   left son=1450 (88 obs) right son=1451 (11 obs)
##   Primary splits:
##       age               < 73.5   to the left,  improve=3.2020200, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.8723440, (0 missing)
##       depression        < 0.5    to the left,  improve=1.3986170, (0 missing)
##       reimbursement2008 < 1495   to the left,  improve=0.6074520, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.4981241, (0 missing)
## 
## Node number 726: 17 observations
##   predicted class=B1  expected loss=0.3529412  P(node) =0.00085
##     class counts:    11     4     1     1     0
##    probabilities: 0.647 0.235 0.059 0.059 0.000 
## 
## Node number 727: 12 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0006
##     class counts:     3     6     2     1     0
##    probabilities: 0.250 0.500 0.167 0.083 0.000 
## 
## Node number 736: 455 observations
##   predicted class=B1  expected loss=0.2307692  P(node) =0.02275
##     class counts:   350    70    26     7     2
##    probabilities: 0.769 0.154 0.057 0.015 0.004 
## 
## Node number 737: 173 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3236994  P(node) =0.00865
##     class counts:   117    34    17     5     0
##    probabilities: 0.676 0.197 0.098 0.029 0.000 
##   left son=1474 (145 obs) right son=1475 (28 obs)
##   Primary splits:
##       reimbursement2008 < 820    to the right, improve=2.1496140, (0 missing)
##       copd              < 0.5    to the right, improve=1.2566750, (0 missing)
##       age               < 51     to the left,  improve=0.8052618, (0 missing)
##       depression        < 0.5    to the right, improve=0.7128829, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.2397510, (0 missing)
## 
## Node number 738: 52 observations
##   predicted class=B1  expected loss=0.3076923  P(node) =0.0026
##     class counts:    36    10     5     1     0
##    probabilities: 0.692 0.192 0.096 0.019 0.000 
## 
## Node number 739: 11 observations
##   predicted class=B2  expected loss=0.5454545  P(node) =0.00055
##     class counts:     4     5     2     0     0
##    probabilities: 0.364 0.455 0.182 0.000 0.000 
## 
## Node number 748: 28 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.0014
##     class counts:    16     7     2     3     0
##    probabilities: 0.571 0.250 0.071 0.107 0.000 
## 
## Node number 749: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     2     2     3     0     0
##    probabilities: 0.286 0.286 0.429 0.000 0.000 
## 
## Node number 756: 213 observations,    complexity param=6.084576e-05
##   predicted class=B1  expected loss=0.286385  P(node) =0.01065
##     class counts:   152    40    17     3     1
##    probabilities: 0.714 0.188 0.080 0.014 0.005 
##   left son=1512 (74 obs) right son=1513 (139 obs)
##   Primary splits:
##       age               < 79.5   to the right, improve=0.9593750, (0 missing)
##       reimbursement2008 < 1135   to the right, improve=0.8732722, (0 missing)
##       kidney            < 0.5    to the right, improve=0.6032588, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.5388738, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5312397, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1145   to the right, agree=0.676, adj=0.068, (0 split)
## 
## Node number 757: 97 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3917526  P(node) =0.00485
##     class counts:    59    25     7     6     0
##    probabilities: 0.608 0.258 0.072 0.062 0.000 
##   left son=1514 (68 obs) right son=1515 (29 obs)
##   Primary splits:
##       age               < 80.5   to the left,  improve=1.6903660, (0 missing)
##       reimbursement2008 < 825    to the left,  improve=1.2122050, (0 missing)
##       kidney            < 0.5    to the right, improve=0.6415946, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.3898343, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3406181, (0 missing)
##   Surrogate splits:
##       arthritis         < 0.5    to the left,  agree=0.711, adj=0.034, (0 split)
##       reimbursement2008 < 695    to the right, agree=0.711, adj=0.034, (0 split)
## 
## Node number 760: 242 observations
##   predicted class=B1  expected loss=0.3719008  P(node) =0.0121
##     class counts:   152    65    13    12     0
##    probabilities: 0.628 0.269 0.054 0.050 0.000 
## 
## Node number 761: 110 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4636364  P(node) =0.0055
##     class counts:    59    28    17     6     0
##    probabilities: 0.536 0.255 0.155 0.055 0.000 
##   left son=1522 (54 obs) right son=1523 (56 obs)
##   Primary splits:
##       age               < 70.5   to the left,  improve=1.6735210, (0 missing)
##       reimbursement2008 < 1215   to the right, improve=1.1616160, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.1244670, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.9812987, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5845740, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1435   to the right, agree=0.573, adj=0.130, (0 split)
##       kidney            < 0.5    to the right, agree=0.536, adj=0.056, (0 split)
##       copd              < 0.5    to the left,  agree=0.527, adj=0.037, (0 split)
##       alzheimers        < 0.5    to the right, agree=0.518, adj=0.019, (0 split)
##       heart.failure     < 0.5    to the right, agree=0.518, adj=0.019, (0 split)
## 
## Node number 762: 22 observations
##   predicted class=B1  expected loss=0.3636364  P(node) =0.0011
##     class counts:    14     2     4     1     1
##    probabilities: 0.636 0.091 0.182 0.045 0.045 
## 
## Node number 763: 8 observations
##   predicted class=B4  expected loss=0.625  P(node) =0.0004
##     class counts:     2     1     2     3     0
##    probabilities: 0.250 0.125 0.250 0.375 0.000 
## 
## Node number 768: 288 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.2743056  P(node) =0.0144
##     class counts:   209    43    28     8     0
##    probabilities: 0.726 0.149 0.097 0.028 0.000 
##   left son=1536 (47 obs) right son=1537 (241 obs)
##   Primary splits:
##       arthritis         < 0.5    to the right, improve=0.8439747, (0 missing)
##       reimbursement2008 < 1655   to the right, improve=0.6696734, (0 missing)
##       age               < 74.5   to the right, improve=0.6381027, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5456723, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.3289436, (0 missing)
## 
## Node number 769: 107 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3738318  P(node) =0.00535
##     class counts:    67    27    11     1     1
##    probabilities: 0.626 0.252 0.103 0.009 0.009 
##   left son=1538 (92 obs) right son=1539 (15 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=1.4783150, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7755357, (0 missing)
##       reimbursement2008 < 2050   to the right, improve=0.7622484, (0 missing)
##       age               < 52.5   to the right, improve=0.7367951, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.6885313, (0 missing)
## 
## Node number 770: 22 observations
##   predicted class=B1  expected loss=0.09090909  P(node) =0.0011
##     class counts:    20     2     0     0     0
##    probabilities: 0.909 0.091 0.000 0.000 0.000 
## 
## Node number 771: 100 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.46  P(node) =0.005
##     class counts:    54    28    11     7     0
##    probabilities: 0.540 0.280 0.110 0.070 0.000 
##   left son=1542 (72 obs) right son=1543 (28 obs)
##   Primary splits:
##       age               < 79.5   to the left,  improve=1.5182540, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.4808320, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.2877110, (0 missing)
##       reimbursement2008 < 2415   to the left,  improve=1.1369950, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.6141026, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2565   to the left,  agree=0.74, adj=0.071, (0 split)
## 
## Node number 778: 66 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.4090909  P(node) =0.0033
##     class counts:    39    23     3     0     1
##    probabilities: 0.591 0.348 0.045 0.000 0.015 
##   left son=1556 (41 obs) right son=1557 (25 obs)
##   Primary splits:
##       age               < 80.5   to the left,  improve=0.7254398, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.4378788, (0 missing)
##       reimbursement2008 < 3315   to the left,  improve=0.4004696, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3326730, (0 missing)
##       depression        < 0.5    to the left,  improve=0.3017677, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.667, adj=0.12, (0 split)
## 
## Node number 779: 7 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.00035
##     class counts:     5     0     1     1     0
##    probabilities: 0.714 0.000 0.143 0.143 0.000 
## 
## Node number 782: 7 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.00035
##     class counts:     4     3     0     0     0
##    probabilities: 0.571 0.429 0.000 0.000 0.000 
## 
## Node number 783: 19 observations
##   predicted class=B2  expected loss=0.3157895  P(node) =0.00095
##     class counts:     4    13     1     1     0
##    probabilities: 0.211 0.684 0.053 0.053 0.000 
## 
## Node number 790: 50 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.46  P(node) =0.0025
##     class counts:    27    16     2     4     1
##    probabilities: 0.540 0.320 0.040 0.080 0.020 
##   left son=1580 (26 obs) right son=1581 (24 obs)
##   Primary splits:
##       age               < 71.5   to the right, improve=1.2069230, (0 missing)
##       reimbursement2008 < 1800   to the right, improve=1.0050000, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.8916550, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.8085714, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2265   to the left,  agree=0.62, adj=0.208, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.56, adj=0.083, (0 split)
## 
## Node number 791: 8 observations
##   predicted class=B2  expected loss=0.625  P(node) =0.0004
##     class counts:     2     3     3     0     0
##    probabilities: 0.250 0.375 0.375 0.000 0.000 
## 
## Node number 794: 9 observations
##   predicted class=B1  expected loss=0.2222222  P(node) =0.00045
##     class counts:     7     1     1     0     0
##    probabilities: 0.778 0.111 0.111 0.000 0.000 
## 
## Node number 795: 121 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5702479  P(node) =0.00605
##     class counts:    52    42    23     3     1
##    probabilities: 0.430 0.347 0.190 0.025 0.008 
##   left son=1590 (113 obs) right son=1591 (8 obs)
##   Primary splits:
##       reimbursement2008 < 3190   to the left,  improve=1.4937290, (0 missing)
##       age               < 83.5   to the left,  improve=1.2045730, (0 missing)
##       arthritis         < 0.5    to the right, improve=1.1497890, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.1433640, (0 missing)
##       cancer            < 0.5    to the right, improve=0.5801522, (0 missing)
## 
## Node number 832: 163 observations
##   predicted class=B1  expected loss=0.3374233  P(node) =0.00815
##     class counts:   108    28    18     8     1
##    probabilities: 0.663 0.172 0.110 0.049 0.006 
## 
## Node number 833: 144 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.4166667  P(node) =0.0072
##     class counts:    84    43    10     6     1
##    probabilities: 0.583 0.299 0.069 0.042 0.007 
##   left son=1666 (86 obs) right son=1667 (58 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=2.003041, (0 missing)
##       reimbursement2008 < 2295   to the left,  improve=1.394463, (0 missing)
##       age               < 96     to the right, improve=1.318865, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.140392, (0 missing)
##       copd              < 0.5    to the left,  improve=1.104582, (0 missing)
##   Surrogate splits:
##       kidney            < 0.5    to the left,  agree=0.632, adj=0.086, (0 split)
##       age               < 84.5   to the left,  agree=0.618, adj=0.052, (0 split)
##       reimbursement2008 < 2475   to the left,  agree=0.604, adj=0.017, (0 split)
## 
## Node number 834: 11 observations
##   predicted class=B1  expected loss=0.1818182  P(node) =0.00055
##     class counts:     9     1     1     0     0
##    probabilities: 0.818 0.091 0.091 0.000 0.000 
## 
## Node number 835: 88 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.5113636  P(node) =0.0044
##     class counts:    43    33     6     5     1
##    probabilities: 0.489 0.375 0.068 0.057 0.011 
##   left son=1670 (63 obs) right son=1671 (25 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=1.364329, (0 missing)
##       age               < 88.5   to the left,  improve=1.315651, (0 missing)
##       reimbursement2008 < 1675   to the right, improve=1.302389, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.227954, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.034774, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1665   to the right, agree=0.739, adj=0.08, (0 split)
## 
## Node number 836: 228 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.4078947  P(node) =0.0114
##     class counts:   135    61    20    11     1
##    probabilities: 0.592 0.268 0.088 0.048 0.004 
##   left son=1672 (218 obs) right son=1673 (10 obs)
##   Primary splits:
##       age               < 43.5   to the right, improve=2.3332050, (0 missing)
##       reimbursement2008 < 2485   to the left,  improve=2.1917580, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.7231690, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4130781, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3314113, (0 missing)
## 
## Node number 837: 33 observations,    complexity param=0.000380286
##   predicted class=B2  expected loss=0.6363636  P(node) =0.00165
##     class counts:     9    12     8     4     0
##    probabilities: 0.273 0.364 0.242 0.121 0.000 
##   left son=1674 (26 obs) right son=1675 (7 obs)
##   Primary splits:
##       age               < 72.5   to the left,  improve=2.8235100, (0 missing)
##       reimbursement2008 < 2185   to the right, improve=1.9883450, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.3051950, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.9114219, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5432900, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.848, adj=0.286, (0 split)
## 
## Node number 838: 146 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5821918  P(node) =0.0073
##     class counts:    56    61    19     8     2
##    probabilities: 0.384 0.418 0.130 0.055 0.014 
##   left son=1676 (115 obs) right son=1677 (31 obs)
##   Primary splits:
##       reimbursement2008 < 2235   to the left,  improve=1.5612480, (0 missing)
##       age               < 57     to the right, improve=1.4223930, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.7955683, (0 missing)
##       cancer            < 0.5    to the right, improve=0.5672709, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4457929, (0 missing)
## 
## Node number 839: 36 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.5833333  P(node) =0.0018
##     class counts:    15     7    10     3     1
##    probabilities: 0.417 0.194 0.278 0.083 0.028 
##   left son=1678 (11 obs) right son=1679 (25 obs)
##   Primary splits:
##       age               < 69.5   to the right, improve=1.3915150, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.1487180, (0 missing)
##       reimbursement2008 < 1805   to the left,  improve=1.0180620, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.8888889, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.2095875, (0 missing)
## 
## Node number 856: 76 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.3684211  P(node) =0.0038
##     class counts:    48    18     4     5     1
##    probabilities: 0.632 0.237 0.053 0.066 0.013 
##   left son=1712 (62 obs) right son=1713 (14 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=1.9467620, (0 missing)
##       reimbursement2008 < 1865   to the right, improve=1.2898500, (0 missing)
##       age               < 65.5   to the right, improve=1.1346230, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.9830044, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8057033, (0 missing)
## 
## Node number 857: 86 observations,    complexity param=0.0006084576
##   predicted class=B2  expected loss=0.5930233  P(node) =0.0043
##     class counts:    28    35    16     7     0
##    probabilities: 0.326 0.407 0.186 0.081 0.000 
##   left son=1714 (54 obs) right son=1715 (32 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=2.0120050, (0 missing)
##       reimbursement2008 < 2425   to the right, improve=1.7270100, (0 missing)
##       age               < 62.5   to the right, improve=1.4082940, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.0133720, (0 missing)
##       kidney            < 0.5    to the right, improve=0.7368141, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1995   to the right, agree=0.64, adj=0.031, (0 split)
## 
## Node number 858: 117 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.4871795  P(node) =0.00585
##     class counts:    39    60    17     1     0
##    probabilities: 0.333 0.513 0.145 0.009 0.000 
##   left son=1716 (8 obs) right son=1717 (109 obs)
##   Primary splits:
##       reimbursement2008 < 2445   to the right, improve=1.3278250, (0 missing)
##       age               < 77.5   to the right, improve=0.8223648, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.6487584, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5676773, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.3698183, (0 missing)
## 
## Node number 859: 19 observations
##   predicted class=B1  expected loss=0.6315789  P(node) =0.00095
##     class counts:     7     4     6     2     0
##    probabilities: 0.368 0.211 0.316 0.105 0.000 
## 
## Node number 864: 21 observations
##   predicted class=B1  expected loss=0.1428571  P(node) =0.00105
##     class counts:    18     2     0     1     0
##    probabilities: 0.857 0.095 0.000 0.048 0.000 
## 
## Node number 865: 47 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4468085  P(node) =0.00235
##     class counts:    26    16     3     2     0
##    probabilities: 0.553 0.340 0.064 0.043 0.000 
##   left son=1730 (37 obs) right son=1731 (10 obs)
##   Primary splits:
##       reimbursement2008 < 2765   to the right, improve=1.2287520, (0 missing)
##       depression        < 0.5    to the left,  improve=1.1399940, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.1047280, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7825059, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.7595591, (0 missing)
## 
## Node number 866: 92 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.3804348  P(node) =0.0046
##     class counts:    57    21    10     4     0
##    probabilities: 0.620 0.228 0.109 0.043 0.000 
##   left son=1732 (23 obs) right son=1733 (69 obs)
##   Primary splits:
##       reimbursement2008 < 3170   to the right, improve=1.9927540, (0 missing)
##       age               < 83.5   to the left,  improve=1.0853600, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.0471420, (0 missing)
##       copd              < 0.5    to the left,  improve=0.9387681, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.5135517, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the right, agree=0.848, adj=0.391, (0 split)
##       age        < 89.5   to the right, agree=0.761, adj=0.043, (0 split)
## 
## Node number 867: 121 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.5619835  P(node) =0.00605
##     class counts:    53    39    22     5     2
##    probabilities: 0.438 0.322 0.182 0.041 0.017 
##   left son=1734 (104 obs) right son=1735 (17 obs)
##   Primary splits:
##       age               < 69.5   to the right, improve=2.7636680, (0 missing)
##       reimbursement2008 < 2675   to the left,  improve=1.1093730, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.9745305, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.9029175, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5339984, (0 missing)
## 
## Node number 872: 133 observations,    complexity param=0.0006084576
##   predicted class=B1  expected loss=0.5263158  P(node) =0.00665
##     class counts:    63    48    11    11     0
##    probabilities: 0.474 0.361 0.083 0.083 0.000 
##   left son=1744 (8 obs) right son=1745 (125 obs)
##   Primary splits:
##       reimbursement2008 < 3365   to the right, improve=1.9610380, (0 missing)
##       age               < 69.5   to the left,  improve=1.5783450, (0 missing)
##       depression        < 0.5    to the left,  improve=1.1410180, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.9988038, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.7504819, (0 missing)
## 
## Node number 873: 13 observations
##   predicted class=B3  expected loss=0.6153846  P(node) =0.00065
##     class counts:     2     4     5     2     0
##    probabilities: 0.154 0.308 0.385 0.154 0.000 
## 
## Node number 874: 11 observations
##   predicted class=B1  expected loss=0.5454545  P(node) =0.00055
##     class counts:     5     2     3     1     0
##    probabilities: 0.455 0.182 0.273 0.091 0.000 
## 
## Node number 875: 56 observations,    complexity param=0.0003549336
##   predicted class=B2  expected loss=0.625  P(node) =0.0028
##     class counts:    13    21    14     8     0
##    probabilities: 0.232 0.375 0.250 0.143 0.000 
##   left son=1750 (10 obs) right son=1751 (46 obs)
##   Primary splits:
##       reimbursement2008 < 2755   to the left,  improve=1.7947200, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6517857, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5812448, (0 missing)
##       age               < 82.5   to the right, improve=0.5119048, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=0.1398924, (0 missing)
## 
## Node number 876: 41 observations
##   predicted class=B2  expected loss=0.3902439  P(node) =0.00205
##     class counts:     9    25     6     1     0
##    probabilities: 0.220 0.610 0.146 0.024 0.000 
## 
## Node number 877: 16 observations
##   predicted class=B1  expected loss=0.5625  P(node) =0.0008
##     class counts:     7     4     3     2     0
##    probabilities: 0.438 0.250 0.188 0.125 0.000 
## 
## Node number 878: 9 observations
##   predicted class=B1  expected loss=0.5555556  P(node) =0.00045
##     class counts:     4     2     3     0     0
##    probabilities: 0.444 0.222 0.333 0.000 0.000 
## 
## Node number 879: 18 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.0009
##     class counts:     0    10     8     0     0
##    probabilities: 0.000 0.556 0.444 0.000 0.000 
## 
## Node number 880: 142 observations,    complexity param=0.0002788764
##   predicted class=B2  expected loss=0.5704225  P(node) =0.0071
##     class counts:    49    61    27     4     1
##    probabilities: 0.345 0.430 0.190 0.028 0.007 
##   left son=1760 (104 obs) right son=1761 (38 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=1.5963530, (0 missing)
##       reimbursement2008 < 2805   to the right, improve=1.3502880, (0 missing)
##       copd              < 0.5    to the left,  improve=1.1429120, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.0117310, (0 missing)
##       age               < 66.5   to the left,  improve=0.9566806, (0 missing)
## 
## Node number 881: 8 observations
##   predicted class=B2  expected loss=0.25  P(node) =0.0004
##     class counts:     1     6     0     1     0
##    probabilities: 0.125 0.750 0.000 0.125 0.000 
## 
## Node number 888: 40 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.575  P(node) =0.002
##     class counts:    17    16     5     1     1
##    probabilities: 0.425 0.400 0.125 0.025 0.025 
##   left son=1776 (11 obs) right son=1777 (29 obs)
##   Primary splits:
##       age               < 82.5   to the right, improve=1.2360500, (0 missing)
##       copd              < 0.5    to the left,  improve=1.0506490, (0 missing)
##       reimbursement2008 < 3215   to the right, improve=0.7666667, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.7606061, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.5901099, (0 missing)
## 
## Node number 889: 30 observations
##   predicted class=B2  expected loss=0.3666667  P(node) =0.0015
##     class counts:     5    19     3     3     0
##    probabilities: 0.167 0.633 0.100 0.100 0.000 
## 
## Node number 896: 26 observations
##   predicted class=B1  expected loss=0.07692308  P(node) =0.0013
##     class counts:    24     1     1     0     0
##    probabilities: 0.923 0.038 0.038 0.000 0.000 
## 
## Node number 897: 94 observations,    complexity param=0.0001014096
##   predicted class=B1  expected loss=0.3297872  P(node) =0.0047
##     class counts:    63    20     7     4     0
##    probabilities: 0.670 0.213 0.074 0.043 0.000 
##   left son=1794 (64 obs) right son=1795 (30 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=1.4985370, (0 missing)
##       age               < 49.5   to the right, improve=1.2949040, (0 missing)
##       reimbursement2008 < 3800   to the left,  improve=1.1582080, (0 missing)
##       copd              < 0.5    to the left,  improve=0.9964539, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.4900436, (0 missing)
##   Surrogate splits:
##       age               < 91.5   to the left,  agree=0.723, adj=0.133, (0 split)
##       stroke            < 0.5    to the left,  agree=0.723, adj=0.133, (0 split)
##       copd              < 0.5    to the left,  agree=0.702, adj=0.067, (0 split)
##       reimbursement2008 < 7705   to the left,  agree=0.691, adj=0.033, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.691, adj=0.033, (0 split)
## 
## Node number 898: 89 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3595506  P(node) =0.00445
##     class counts:    57    21     7     3     1
##    probabilities: 0.640 0.236 0.079 0.034 0.011 
##   left son=1796 (22 obs) right son=1797 (67 obs)
##   Primary splits:
##       reimbursement2008 < 9310   to the left,  improve=2.1396340, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.6199640, (0 missing)
##       copd              < 0.5    to the left,  improve=0.9273400, (0 missing)
##       age               < 59.5   to the right, improve=0.8270218, (0 missing)
##       stroke            < 0.5    to the right, improve=0.8268807, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.865, adj=0.455, (0 split)
##       age        < 94.5   to the right, agree=0.775, adj=0.091, (0 split)
## 
## Node number 899: 121 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.4958678  P(node) =0.00605
##     class counts:    61    35    21     3     1
##    probabilities: 0.504 0.289 0.174 0.025 0.008 
##   left son=1798 (105 obs) right son=1799 (16 obs)
##   Primary splits:
##       reimbursement2008 < 6145   to the left,  improve=3.6574090, (0 missing)
##       age               < 88.5   to the right, improve=1.6732430, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.4740051, (0 missing)
##       kidney            < 0.5    to the right, improve=0.3966942, (0 missing)
##       copd              < 0.5    to the left,  improve=0.2864993, (0 missing)
## 
## Node number 902: 60 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.5  P(node) =0.003
##     class counts:    30    23     5     2     0
##    probabilities: 0.500 0.383 0.083 0.033 0.000 
##   left son=1804 (26 obs) right son=1805 (34 obs)
##   Primary splits:
##       age               < 74.5   to the left,  improve=1.7361990, (0 missing)
##       reimbursement2008 < 9210   to the right, improve=1.6200000, (0 missing)
##       ihd               < 0.5    to the right, improve=1.1258370, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.5012422, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.4916667, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 3905   to the left,  agree=0.667, adj=0.231, (0 split)
##       stroke            < 0.5    to the right, agree=0.600, adj=0.077, (0 split)
## 
## Node number 903: 14 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.0007
##     class counts:     3    10     0     0     1
##    probabilities: 0.214 0.714 0.000 0.000 0.071 
## 
## Node number 906: 16 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0008
##     class counts:     5     8     3     0     0
##    probabilities: 0.312 0.500 0.188 0.000 0.000 
## 
## Node number 907: 15 observations
##   predicted class=B1  expected loss=0.5333333  P(node) =0.00075
##     class counts:     7     3     4     1     0
##    probabilities: 0.467 0.200 0.267 0.067 0.000 
## 
## Node number 910: 18 observations
##   predicted class=B2  expected loss=0.3888889  P(node) =0.0009
##     class counts:     4    11     3     0     0
##    probabilities: 0.222 0.611 0.167 0.000 0.000 
## 
## Node number 911: 54 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.6666667  P(node) =0.0027
##     class counts:    18    18    16     2     0
##    probabilities: 0.333 0.333 0.296 0.037 0.000 
##   left son=1822 (22 obs) right son=1823 (32 obs)
##   Primary splits:
##       reimbursement2008 < 13120  to the right, improve=1.9920030, (0 missing)
##       copd              < 0.5    to the right, improve=1.6851850, (0 missing)
##       kidney            < 0.5    to the right, improve=0.7220273, (0 missing)
##       age               < 81.5   to the right, improve=0.6681397, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.4629630, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.796, adj=0.500, (0 split)
##       age        < 94.5   to the right, agree=0.667, adj=0.182, (0 split)
##       kidney     < 0.5    to the right, agree=0.611, adj=0.045, (0 split)
## 
## Node number 914: 25 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.48  P(node) =0.00125
##     class counts:    13     7     0     5     0
##    probabilities: 0.520 0.280 0.000 0.200 0.000 
##   left son=1828 (18 obs) right son=1829 (7 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=1.3911110, (0 missing)
##       age               < 71.5   to the right, improve=0.7994805, (0 missing)
##       reimbursement2008 < 5140   to the left,  improve=0.6774359, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.3059740, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 5705   to the left,  agree=0.76, adj=0.143, (0 split)
## 
## Node number 915: 7 observations
##   predicted class=B1  expected loss=0.5714286  P(node) =0.00035
##     class counts:     3     1     3     0     0
##    probabilities: 0.429 0.143 0.429 0.000 0.000 
## 
## Node number 936: 27 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4074074  P(node) =0.00135
##     class counts:    16     8     2     1     0
##    probabilities: 0.593 0.296 0.074 0.037 0.000 
##   left son=1872 (11 obs) right son=1873 (16 obs)
##   Primary splits:
##       reimbursement2008 < 14045  to the right, improve=1.6334180, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.3152360, (0 missing)
##       kidney            < 0.5    to the right, improve=0.9629630, (0 missing)
##       age               < 69.5   to the right, improve=0.8518519, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7261209, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.778, adj=0.455, (0 split)
##       age        < 77.5   to the right, agree=0.704, adj=0.273, (0 split)
## 
## Node number 937: 45 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.4222222  P(node) =0.00225
##     class counts:    12    26     5     2     0
##    probabilities: 0.267 0.578 0.111 0.044 0.000 
##   left son=1874 (7 obs) right son=1875 (38 obs)
##   Primary splits:
##       reimbursement2008 < 3740   to the left,  improve=1.5017540, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7257703, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.6939394, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5049550, (0 missing)
##       kidney            < 0.5    to the right, improve=0.4306306, (0 missing)
## 
## Node number 938: 12 observations
##   predicted class=B2  expected loss=0.1666667  P(node) =0.0006
##     class counts:     1    10     1     0     0
##    probabilities: 0.083 0.833 0.083 0.000 0.000 
## 
## Node number 939: 52 observations,    complexity param=0.0003549336
##   predicted class=B2  expected loss=0.5769231  P(node) =0.0026
##     class counts:    11    22    15     4     0
##    probabilities: 0.212 0.423 0.288 0.077 0.000 
##   left son=1878 (13 obs) right son=1879 (39 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=2.0897440, (0 missing)
##       age               < 79.5   to the right, improve=1.0514040, (0 missing)
##       reimbursement2008 < 5860   to the right, improve=1.0026590, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.9019404, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.6196581, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 3925   to the left,  agree=0.769, adj=0.077, (0 split)
## 
## Node number 940: 13 observations
##   predicted class=B1  expected loss=0.2307692  P(node) =0.00065
##     class counts:    10     2     1     0     0
##    probabilities: 0.769 0.154 0.077 0.000 0.000 
## 
## Node number 941: 33 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.6363636  P(node) =0.00165
##     class counts:    12     7     9     5     0
##    probabilities: 0.364 0.212 0.273 0.152 0.000 
##   left son=1882 (26 obs) right son=1883 (7 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=1.4778550, (0 missing)
##       reimbursement2008 < 10080  to the left,  improve=1.4293940, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.9393939, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7727273, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7575758, (0 missing)
## 
## Node number 956: 41 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.6097561  P(node) =0.00205
##     class counts:    11    16    10     4     0
##    probabilities: 0.268 0.390 0.244 0.098 0.000 
##   left son=1912 (30 obs) right son=1913 (11 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=1.8119730, (0 missing)
##       reimbursement2008 < 5410   to the left,  improve=1.1877310, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.8998522, (0 missing)
##       age               < 70.5   to the right, improve=0.8138451, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.7968658, (0 missing)
##   Surrogate splits:
##       age    < 37     to the right, agree=0.756, adj=0.091, (0 split)
##       stroke < 0.5    to the left,  agree=0.756, adj=0.091, (0 split)
## 
## Node number 957: 38 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.5  P(node) =0.0019
##     class counts:     4    19    13     2     0
##    probabilities: 0.105 0.500 0.342 0.053 0.000 
##   left son=1914 (31 obs) right son=1915 (7 obs)
##   Primary splits:
##       reimbursement2008 < 4300   to the right, improve=2.3189430, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.0000000, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.9492850, (0 missing)
##       age               < 81.5   to the left,  improve=0.7535885, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.6058612, (0 missing)
##   Surrogate splits:
##       age < 92.5   to the left,  agree=0.842, adj=0.143, (0 split)
## 
## Node number 960: 155 observations,    complexity param=0.0003422574
##   predicted class=B1  expected loss=0.5032258  P(node) =0.00775
##     class counts:    77    47    28     3     0
##    probabilities: 0.497 0.303 0.181 0.019 0.000 
##   left son=1920 (32 obs) right son=1921 (123 obs)
##   Primary splits:
##       reimbursement2008 < 6290   to the right, improve=1.7144870, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.3927660, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.5998232, (0 missing)
##       age               < 66.5   to the left,  improve=0.5282028, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.2484000, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.852, adj=0.281, (0 split)
## 
## Node number 961: 44 observations
##   predicted class=B2  expected loss=0.4318182  P(node) =0.0022
##     class counts:    13    25     4     2     0
##    probabilities: 0.295 0.568 0.091 0.045 0.000 
## 
## Node number 962: 52 observations,    complexity param=0.000507048
##   predicted class=B1  expected loss=0.6923077  P(node) =0.0026
##     class counts:    16    16     9    10     1
##    probabilities: 0.308 0.308 0.173 0.192 0.019 
##   left son=1924 (31 obs) right son=1925 (21 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=1.6461660, (0 missing)
##       age               < 52     to the right, improve=1.5856640, (0 missing)
##       reimbursement2008 < 13440  to the right, improve=1.1403330, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.9728254, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7932401, (0 missing)
##   Surrogate splits:
##       age               < 50.5   to the right, agree=0.654, adj=0.143, (0 split)
##       stroke            < 0.5    to the left,  agree=0.654, adj=0.143, (0 split)
##       depression        < 0.5    to the left,  agree=0.635, adj=0.095, (0 split)
##       reimbursement2008 < 16130  to the left,  agree=0.615, adj=0.048, (0 split)
## 
## Node number 963: 26 observations,    complexity param=0.0001521144
##   predicted class=B3  expected loss=0.5769231  P(node) =0.0013
##     class counts:     8     3    11     4     0
##    probabilities: 0.308 0.115 0.423 0.154 0.000 
##   left son=1926 (15 obs) right son=1927 (11 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=1.1109560, (0 missing)
##       reimbursement2008 < 10135  to the right, improve=0.9468864, (0 missing)
##       age               < 65     to the right, improve=0.5480769, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5064103, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.4720965, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 9215   to the right, agree=0.692, adj=0.273, (0 split)
##       age               < 68.5   to the left,  agree=0.654, adj=0.182, (0 split)
##       stroke            < 0.5    to the left,  agree=0.654, adj=0.182, (0 split)
##       ihd               < 0.5    to the right, agree=0.615, adj=0.091, (0 split)
## 
## Node number 964: 170 observations,    complexity param=0.0004563432
##   predicted class=B1  expected loss=0.5411765  P(node) =0.0085
##     class counts:    78    58    23    10     1
##    probabilities: 0.459 0.341 0.135 0.059 0.006 
##   left son=1928 (144 obs) right son=1929 (26 obs)
##   Primary splits:
##       age               < 88.5   to the left,  improve=2.0616640, (0 missing)
##       reimbursement2008 < 5215   to the left,  improve=1.6700280, (0 missing)
##       copd              < 0.5    to the right, improve=0.6860574, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6145002, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.5698065, (0 missing)
## 
## Node number 965: 157 observations,    complexity param=0.0008746577
##   predicted class=B2  expected loss=0.5732484  P(node) =0.00785
##     class counts:    49    67    27    12     2
##    probabilities: 0.312 0.427 0.172 0.076 0.013 
##   left son=1930 (28 obs) right son=1931 (129 obs)
##   Primary splits:
##       age        < 88.5   to the right, improve=2.733535, (0 missing)
##       copd       < 0.5    to the left,  improve=2.275853, (0 missing)
##       alzheimers < 0.5    to the left,  improve=1.745083, (0 missing)
##       ihd        < 0.5    to the left,  improve=1.711287, (0 missing)
##       stroke     < 0.5    to the left,  improve=1.709726, (0 missing)
## 
## Node number 966: 74 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.3513514  P(node) =0.0037
##     class counts:    17    48     7     2     0
##    probabilities: 0.230 0.649 0.095 0.027 0.000 
##   left son=1932 (64 obs) right son=1933 (10 obs)
##   Primary splits:
##       reimbursement2008 < 4725   to the left,  improve=2.1494930, (0 missing)
##       age               < 72.5   to the left,  improve=1.9802800, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.4229040, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5439425, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3682432, (0 missing)
## 
## Node number 967: 113 observations,    complexity param=0.000380286
##   predicted class=B2  expected loss=0.5221239  P(node) =0.00565
##     class counts:    34    54    20     5     0
##    probabilities: 0.301 0.478 0.177 0.044 0.000 
##   left son=1934 (9 obs) right son=1935 (104 obs)
##   Primary splits:
##       age               < 78.5   to the left,  improve=2.662942, (0 missing)
##       depression        < 0.5    to the right, improve=2.539583, (0 missing)
##       stroke            < 0.5    to the right, improve=1.321986, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.244120, (0 missing)
##       reimbursement2008 < 4030   to the left,  improve=0.939590, (0 missing)
## 
## Node number 972: 8 observations
##   predicted class=B2  expected loss=0.125  P(node) =0.0004
##     class counts:     1     7     0     0     0
##    probabilities: 0.125 0.875 0.000 0.000 0.000 
## 
## Node number 973: 112 observations,    complexity param=0.0005324004
##   predicted class=B2  expected loss=0.6517857  P(node) =0.0056
##     class counts:    24    39    38    11     0
##    probabilities: 0.214 0.348 0.339 0.098 0.000 
##   left son=1946 (49 obs) right son=1947 (63 obs)
##   Primary splits:
##       age               < 71.5   to the left,  improve=1.734410, (0 missing)
##       reimbursement2008 < 6810   to the left,  improve=1.588784, (0 missing)
##       depression        < 0.5    to the left,  improve=1.542396, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.169209, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.109144, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 24415  to the right, agree=0.58, adj=0.041, (0 split)
## 
## Node number 984: 56 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.625  P(node) =0.0028
##     class counts:    21    20     6     6     3
##    probabilities: 0.375 0.357 0.107 0.107 0.054 
##   left son=1968 (38 obs) right son=1969 (18 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.4889310, (0 missing)
##       age               < 68.5   to the right, improve=2.0304350, (0 missing)
##       reimbursement2008 < 14115  to the left,  improve=1.8107140, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=0.9375588, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5983261, (0 missing)
##   Surrogate splits:
##       age               < 57     to the right, agree=0.714, adj=0.111, (0 split)
##       reimbursement2008 < 60180  to the left,  agree=0.714, adj=0.111, (0 split)
##       bucket2008        < 4.5    to the left,  agree=0.714, adj=0.111, (0 split)
## 
## Node number 985: 127 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.519685  P(node) =0.00635
##     class counts:    31    61    17    17     1
##    probabilities: 0.244 0.480 0.134 0.134 0.008 
##   left son=1970 (85 obs) right son=1971 (42 obs)
##   Primary splits:
##       reimbursement2008 < 6240   to the left,  improve=2.0896490, (0 missing)
##       age               < 67.5   to the left,  improve=1.6822110, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.2999880, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.1106320, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.8561487, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.803, adj=0.405, (0 split)
##       cancer     < 0.5    to the left,  agree=0.685, adj=0.048, (0 split)
## 
## Node number 986: 37 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5945946  P(node) =0.00185
##     class counts:    10    15     5     7     0
##    probabilities: 0.270 0.405 0.135 0.189 0.000 
##   left son=1972 (16 obs) right son=1973 (21 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=1.7162160, (0 missing)
##       age               < 84.5   to the right, improve=1.4384380, (0 missing)
##       copd              < 0.5    to the right, improve=1.2456280, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.0857810, (0 missing)
##       reimbursement2008 < 6875   to the right, improve=0.7102638, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 7200   to the left,  agree=0.703, adj=0.313, (0 split)
##       ihd               < 0.5    to the left,  agree=0.649, adj=0.188, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.649, adj=0.188, (0 split)
##       copd              < 0.5    to the left,  agree=0.595, adj=0.063, (0 split)
## 
## Node number 987: 62 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4032258  P(node) =0.0031
##     class counts:     6    37    16     3     0
##    probabilities: 0.097 0.597 0.258 0.048 0.000 
##   left son=1974 (17 obs) right son=1975 (45 obs)
##   Primary splits:
##       reimbursement2008 < 9010   to the right, improve=1.1586340, (0 missing)
##       age               < 64.5   to the right, improve=0.9974302, (0 missing)
##       cancer            < 0.5    to the right, improve=0.9645161, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5071025, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4342640, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.919, adj=0.706, (0 split)
## 
## Node number 988: 16 observations
##   predicted class=B2  expected loss=0.3125  P(node) =0.0008
##     class counts:     3    11     2     0     0
##    probabilities: 0.188 0.688 0.125 0.000 0.000 
## 
## Node number 989: 225 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.56  P(node) =0.01125
##     class counts:    43    99    60    21     2
##    probabilities: 0.191 0.440 0.267 0.093 0.009 
##   left son=1978 (216 obs) right son=1979 (9 obs)
##   Primary splits:
##       reimbursement2008 < 39120  to the left,  improve=1.9111110, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.5225480, (0 missing)
##       age               < 71.5   to the right, improve=0.9369227, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.9367521, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.7079276, (0 missing)
##   Surrogate splits:
##       bucket2008 < 4.5    to the left,  agree=0.969, adj=0.222, (0 split)
## 
## Node number 992: 67 observations,    complexity param=0.000507048
##   predicted class=B1  expected loss=0.6716418  P(node) =0.00335
##     class counts:    22    18    21     4     2
##    probabilities: 0.328 0.269 0.313 0.060 0.030 
##   left son=1984 (43 obs) right son=1985 (24 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=1.596523, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.434701, (0 missing)
##       reimbursement2008 < 8080   to the left,  improve=1.256193, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.048920, (0 missing)
##       age               < 96.5   to the left,  improve=1.002126, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.672, adj=0.083, (0 split)
##       ihd    < 0.5    to the right, agree=0.657, adj=0.042, (0 split)
## 
## Node number 993: 279 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6344086  P(node) =0.01395
##     class counts:    66   102    50    53     8
##    probabilities: 0.237 0.366 0.179 0.190 0.029 
##   left son=1986 (11 obs) right son=1987 (268 obs)
##   Primary splits:
##       reimbursement2008 < 6780   to the left,  improve=2.133825, (0 missing)
##       age               < 77.5   to the left,  improve=1.516129, (0 missing)
##       stroke            < 0.5    to the right, improve=1.276040, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.116912, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.035800, (0 missing)
## 
## Node number 994: 19 observations
##   predicted class=B2  expected loss=0.2631579  P(node) =0.00095
##     class counts:     3    14     1     1     0
##    probabilities: 0.158 0.737 0.053 0.053 0.000 
## 
## Node number 995: 247 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6153846  P(node) =0.01235
##     class counts:    47    95    67    32     6
##    probabilities: 0.190 0.385 0.271 0.130 0.024 
##   left son=1990 (235 obs) right son=1991 (12 obs)
##   Primary splits:
##       age               < 88.5   to the left,  improve=2.7973120, (0 missing)
##       reimbursement2008 < 6170   to the left,  improve=2.4372470, (0 missing)
##       depression        < 0.5    to the right, improve=0.9399906, (0 missing)
##       ihd               < 0.5    to the right, improve=0.8524106, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.7164122, (0 missing)
## 
## Node number 1002: 107 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.3925234  P(node) =0.00535
##     class counts:    16    65    15    10     1
##    probabilities: 0.150 0.607 0.140 0.093 0.009 
##   left son=2004 (88 obs) right son=2005 (19 obs)
##   Primary splits:
##       reimbursement2008 < 4595   to the left,  improve=1.5568240, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7322522, (0 missing)
##       copd              < 0.5    to the right, improve=0.6210399, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.6176956, (0 missing)
##       age               < 81.5   to the right, improve=0.4955512, (0 missing)
## 
## Node number 1003: 25 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.6  P(node) =0.00125
##     class counts:     4    10     7     4     0
##    probabilities: 0.160 0.400 0.280 0.160 0.000 
##   left son=2006 (16 obs) right son=2007 (9 obs)
##   Primary splits:
##       reimbursement2008 < 4975   to the right, improve=0.9127778, (0 missing)
##       depression        < 0.5    to the left,  improve=0.8119481, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5100000, (0 missing)
##       age               < 66.5   to the right, improve=0.3473016, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.2933333, (0 missing)
##   Surrogate splits:
##       age    < 62.5   to the right, agree=0.80, adj=0.444, (0 split)
##       stroke < 0.5    to the left,  agree=0.68, adj=0.111, (0 split)
## 
## Node number 1004: 16 observations
##   predicted class=B1  expected loss=0.625  P(node) =0.0008
##     class counts:     6     5     3     2     0
##    probabilities: 0.375 0.312 0.188 0.125 0.000 
## 
## Node number 1005: 8 observations
##   predicted class=B3  expected loss=0.375  P(node) =0.0004
##     class counts:     1     2     5     0     0
##    probabilities: 0.125 0.250 0.625 0.000 0.000 
## 
## Node number 1006: 253 observations,    complexity param=0.0002028192
##   predicted class=B2  expected loss=0.5454545  P(node) =0.01265
##     class counts:    29   115    69    35     5
##    probabilities: 0.115 0.455 0.273 0.138 0.020 
##   left son=2012 (35 obs) right son=2013 (218 obs)
##   Primary splits:
##       reimbursement2008 < 6565   to the left,  improve=1.3116340, (0 missing)
##       copd              < 0.5    to the left,  improve=1.0918940, (0 missing)
##       age               < 39     to the left,  improve=0.9539227, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8542281, (0 missing)
##       cancer            < 0.5    to the right, improve=0.8037400, (0 missing)
## 
## Node number 1007: 32 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.375  P(node) =0.0016
##     class counts:     0    20     8     3     1
##    probabilities: 0.000 0.625 0.250 0.094 0.031 
##   left son=2014 (22 obs) right son=2015 (10 obs)
##   Primary splits:
##       reimbursement2008 < 5385   to the right, improve=2.4965910, (0 missing)
##       depression        < 0.5    to the right, improve=1.5511360, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.7271825, (0 missing)
##       age               < 85     to the right, improve=0.5208333, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3541667, (0 missing)
##   Surrogate splits:
##       age < 90.5   to the left,  agree=0.75, adj=0.2, (0 split)
## 
## Node number 1012: 13 observations
##   predicted class=B2  expected loss=0.1538462  P(node) =0.00065
##     class counts:     1    11     0     0     1
##    probabilities: 0.077 0.846 0.000 0.000 0.077 
## 
## Node number 1013: 7 observations
##   predicted class=B4  expected loss=0.4285714  P(node) =0.00035
##     class counts:     0     1     2     4     0
##    probabilities: 0.000 0.143 0.286 0.571 0.000 
## 
## Node number 1016: 95 observations,    complexity param=0.000507048
##   predicted class=B1  expected loss=0.7157895  P(node) =0.00475
##     class counts:    27    23    20    25     0
##    probabilities: 0.284 0.242 0.211 0.263 0.000 
##   left son=2032 (67 obs) right son=2033 (28 obs)
##   Primary splits:
##       reimbursement2008 < 18065  to the right, improve=1.9044550, (0 missing)
##       age               < 86.5   to the left,  improve=1.6124630, (0 missing)
##       bucket2008        < 3.5    to the right, improve=0.8617544, (0 missing)
##       cancer            < 0.5    to the right, improve=0.8550877, (0 missing)
##       stroke            < 0.5    to the right, improve=0.5227689, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.821, adj=0.393, (0 split)
## 
## Node number 1017: 138 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6376812  P(node) =0.0069
##     class counts:    21    50    29    30     8
##    probabilities: 0.152 0.362 0.210 0.217 0.058 
##   left son=2034 (41 obs) right son=2035 (97 obs)
##   Primary splits:
##       reimbursement2008 < 22770  to the right, improve=2.1050500, (0 missing)
##       age               < 73.5   to the left,  improve=1.6683600, (0 missing)
##       stroke            < 0.5    to the right, improve=1.3740260, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.3465420, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9647403, (0 missing)
##   Surrogate splits:
##       age < 40.5   to the left,  agree=0.717, adj=0.049, (0 split)
## 
## Node number 1018: 140 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.5928571  P(node) =0.007
##     class counts:    17    57    38    20     8
##    probabilities: 0.121 0.407 0.271 0.143 0.057 
##   left son=2036 (125 obs) right son=2037 (15 obs)
##   Primary splits:
##       age               < 65     to the right, improve=1.6013330, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.3095240, (0 missing)
##       reimbursement2008 < 16720  to the right, improve=1.2510020, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9871662, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9854436, (0 missing)
## 
## Node number 1019: 23 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.4782609  P(node) =0.00115
##     class counts:     1     5    12     4     1
##    probabilities: 0.043 0.217 0.522 0.174 0.043 
##   left son=2038 (13 obs) right son=2039 (10 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=3.5311040, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.4604740, (0 missing)
##       age               < 79     to the left,  improve=1.2028990, (0 missing)
##       reimbursement2008 < 20175  to the left,  improve=0.3003344, (0 missing)
##       depression        < 0.5    to the right, improve=0.1271410, (0 missing)
##   Surrogate splits:
##       age               < 83.5   to the left,  agree=0.652, adj=0.2, (0 split)
##       cancer            < 0.5    to the left,  agree=0.652, adj=0.2, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.652, adj=0.2, (0 split)
##       reimbursement2008 < 17675  to the left,  agree=0.609, adj=0.1, (0 split)
## 
## Node number 1022: 91 observations,    complexity param=0.0002662002
##   predicted class=B2  expected loss=0.5164835  P(node) =0.00455
##     class counts:     6    44    17    21     3
##    probabilities: 0.066 0.484 0.187 0.231 0.033 
##   left son=2044 (47 obs) right son=2045 (44 obs)
##   Primary splits:
##       age               < 72     to the right, improve=1.4196230, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.2187220, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9937374, (0 missing)
##       stroke            < 0.5    to the right, improve=0.7373929, (0 missing)
##       reimbursement2008 < 31655  to the right, improve=0.7326007, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 27945  to the left,  agree=0.604, adj=0.182, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.582, adj=0.136, (0 split)
##       copd              < 0.5    to the left,  agree=0.571, adj=0.114, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.560, adj=0.091, (0 split)
##       arthritis         < 0.5    to the left,  agree=0.549, adj=0.068, (0 split)
## 
## Node number 1023: 331 observations,    complexity param=0.000507048
##   predicted class=B4  expected loss=0.6827795  P(node) =0.01655
##     class counts:    24   104    80   105    18
##    probabilities: 0.073 0.314 0.242 0.317 0.054 
##   left son=2046 (97 obs) right son=2047 (234 obs)
##   Primary splits:
##       stroke            < 0.5    to the right, improve=1.835692, (0 missing)
##       age               < 34.5   to the left,  improve=1.722335, (0 missing)
##       reimbursement2008 < 52775  to the right, improve=1.679153, (0 missing)
##       bucket2008        < 4.5    to the right, improve=1.290835, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.283171, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 92615  to the right, agree=0.713, adj=0.021, (0 split)
## 
## Node number 1284: 94 observations
##   predicted class=B1  expected loss=0.106383  P(node) =0.0047
##     class counts:    84     5     4     1     0
##    probabilities: 0.894 0.053 0.043 0.011 0.000 
## 
## Node number 1285: 707 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.165488  P(node) =0.03535
##     class counts:   590    68    36    11     2
##    probabilities: 0.835 0.096 0.051 0.016 0.003 
##   left son=2570 (277 obs) right son=2571 (430 obs)
##   Primary splits:
##       reimbursement2008 < 495    to the right, improve=0.7004222, (0 missing)
##       age               < 83.5   to the right, improve=0.4988776, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.3588292, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.3154163, (0 missing)
##       depression        < 0.5    to the left,  improve=0.3116005, (0 missing)
##   Surrogate splits:
##       heart.failure < 0.5    to the right, agree=0.611, adj=0.007, (0 split)
##       ihd           < 0.5    to the right, agree=0.610, adj=0.004, (0 split)
## 
## Node number 1414: 43 observations
##   predicted class=B1  expected loss=0.2790698  P(node) =0.00215
##     class counts:    31     6     3     3     0
##    probabilities: 0.721 0.140 0.070 0.070 0.000 
## 
## Node number 1415: 14 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0007
##     class counts:     5     7     0     2     0
##    probabilities: 0.357 0.500 0.000 0.143 0.000 
## 
## Node number 1420: 9 observations
##   predicted class=B1  expected loss=0.1111111  P(node) =0.00045
##     class counts:     8     0     0     1     0
##    probabilities: 0.889 0.000 0.000 0.111 0.000 
## 
## Node number 1421: 67 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2985075  P(node) =0.00335
##     class counts:    47    16     3     1     0
##    probabilities: 0.701 0.239 0.045 0.015 0.000 
##   left son=2842 (60 obs) right son=2843 (7 obs)
##   Primary splits:
##       age               < 78.5   to the left,  improve=1.4644630, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.8523372, (0 missing)
##       kidney            < 0.5    to the right, improve=0.4113964, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.3161117, (0 missing)
##       reimbursement2008 < 775    to the right, improve=0.2780923, (0 missing)
## 
## Node number 1440: 27 observations
##   predicted class=B1  expected loss=0.07407407  P(node) =0.00135
##     class counts:    25     1     1     0     0
##    probabilities: 0.926 0.037 0.037 0.000 0.000 
## 
## Node number 1441: 256 observations,    complexity param=5.07048e-05
##   predicted class=B1  expected loss=0.2265625  P(node) =0.0128
##     class counts:   198    28    21     9     0
##    probabilities: 0.773 0.109 0.082 0.035 0.000 
##   left son=2882 (197 obs) right son=2883 (59 obs)
##   Primary splits:
##       age               < 80.5   to the left,  improve=1.4661490, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.7479467, (0 missing)
##       reimbursement2008 < 1315   to the right, improve=0.5371438, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4432897, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.3477601, (0 missing)
## 
## Node number 1442: 158 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.2721519  P(node) =0.0079
##     class counts:   115    25    13     5     0
##    probabilities: 0.728 0.158 0.082 0.032 0.000 
##   left son=2884 (109 obs) right son=2885 (49 obs)
##   Primary splits:
##       age               < 73.5   to the right, improve=0.6469703, (0 missing)
##       reimbursement2008 < 1375   to the right, improve=0.4601807, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.3961186, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3805342, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.3789804, (0 missing)
## 
## Node number 1443: 8 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0004
##     class counts:     4     3     1     0     0
##    probabilities: 0.500 0.375 0.125 0.000 0.000 
## 
## Node number 1446: 52 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2884615  P(node) =0.0026
##     class counts:    37    10     2     3     0
##    probabilities: 0.712 0.192 0.038 0.058 0.000 
##   left son=2892 (32 obs) right son=2893 (20 obs)
##   Primary splits:
##       reimbursement2008 < 1155   to the right, improve=1.2875000, (0 missing)
##       age               < 65.5   to the right, improve=0.9991597, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.8375000, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6047619, (0 missing)
##       depression        < 0.5    to the right, improve=0.2711712, (0 missing)
##   Surrogate splits:
##       diabetes   < 0.5    to the left,  agree=0.692, adj=0.20, (0 split)
##       copd       < 0.5    to the left,  agree=0.654, adj=0.10, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.635, adj=0.05, (0 split)
## 
## Node number 1447: 35 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.4285714  P(node) =0.00175
##     class counts:    20    14     1     0     0
##    probabilities: 0.571 0.400 0.029 0.000 0.000 
##   left son=2894 (15 obs) right son=2895 (20 obs)
##   Primary splits:
##       diabetes      < 0.5    to the right, improve=1.7761900, (0 missing)
##       age           < 47.5   to the right, improve=1.5857140, (0 missing)
##       heart.failure < 0.5    to the right, improve=0.5724868, (0 missing)
##       depression    < 0.5    to the left,  improve=0.2257519, (0 missing)
##       alzheimers    < 0.5    to the left,  improve=0.1650794, (0 missing)
##   Surrogate splits:
##       arthritis < 0.5    to the right, agree=0.629, adj=0.133, (0 split)
##       age       < 53.5   to the left,  agree=0.600, adj=0.067, (0 split)
## 
## Node number 1450: 88 observations
##   predicted class=B1  expected loss=0.2954545  P(node) =0.0044
##     class counts:    62    17     5     3     1
##    probabilities: 0.705 0.193 0.057 0.034 0.011 
## 
## Node number 1451: 11 observations
##   predicted class=B2  expected loss=0.4545455  P(node) =0.00055
##     class counts:     3     6     2     0     0
##    probabilities: 0.273 0.545 0.182 0.000 0.000 
## 
## Node number 1474: 145 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.2827586  P(node) =0.00725
##     class counts:   104    25    13     3     0
##    probabilities: 0.717 0.172 0.090 0.021 0.000 
##   left son=2948 (8 obs) right son=2949 (137 obs)
##   Primary splits:
##       age               < 51     to the left,  improve=1.0003520, (0 missing)
##       copd              < 0.5    to the right, improve=0.9153314, (0 missing)
##       reimbursement2008 < 855    to the left,  improve=0.8689655, (0 missing)
##       depression        < 0.5    to the right, improve=0.5758972, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.1184309, (0 missing)
## 
## Node number 1475: 28 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.5357143  P(node) =0.0014
##     class counts:    13     9     4     2     0
##    probabilities: 0.464 0.321 0.143 0.071 0.000 
##   left son=2950 (8 obs) right son=2951 (20 obs)
##   Primary splits:
##       age               < 78.5   to the right, improve=1.607143, (0 missing)
##       reimbursement2008 < 795    to the left,  improve=1.046032, (0 missing)
## 
## Node number 1512: 74 observations
##   predicted class=B1  expected loss=0.2297297  P(node) =0.0037
##     class counts:    57     9     5     3     0
##    probabilities: 0.770 0.122 0.068 0.041 0.000 
## 
## Node number 1513: 139 observations,    complexity param=6.084576e-05
##   predicted class=B1  expected loss=0.3165468  P(node) =0.00695
##     class counts:    95    31    12     0     1
##    probabilities: 0.683 0.223 0.086 0.000 0.007 
##   left son=3026 (14 obs) right son=3027 (125 obs)
##   Primary splits:
##       reimbursement2008 < 1105   to the right, improve=1.4099650, (0 missing)
##       age               < 50.5   to the left,  improve=1.1605620, (0 missing)
##       kidney            < 0.5    to the right, improve=0.6624468, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5567975, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.3267556, (0 missing)
##   Surrogate splits:
##       age < 48     to the left,  agree=0.906, adj=0.071, (0 split)
## 
## Node number 1514: 68 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3382353  P(node) =0.0034
##     class counts:    45    13     5     5     0
##    probabilities: 0.662 0.191 0.074 0.074 0.000 
##   left son=3028 (9 obs) right son=3029 (59 obs)
##   Primary splits:
##       kidney            < 0.5    to the right, improve=1.9792840, (0 missing)
##       reimbursement2008 < 755    to the left,  improve=1.0972640, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.6166667, (0 missing)
##       age               < 67.5   to the left,  improve=0.4893617, (0 missing)
##       depression        < 0.5    to the right, improve=0.4750000, (0 missing)
## 
## Node number 1515: 29 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.5172414  P(node) =0.00145
##     class counts:    14    12     2     1     0
##    probabilities: 0.483 0.414 0.069 0.034 0.000 
##   left son=3030 (20 obs) right son=3031 (9 obs)
##   Primary splits:
##       age               < 83.5   to the right, improve=0.59233720, (0 missing)
##       reimbursement2008 < 805    to the right, improve=0.35900380, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.34587250, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.04029038, (0 missing)
## 
## Node number 1522: 54 observations
##   predicted class=B1  expected loss=0.3703704  P(node) =0.0027
##     class counts:    34    10     6     4     0
##    probabilities: 0.630 0.185 0.111 0.074 0.000 
## 
## Node number 1523: 56 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5535714  P(node) =0.0028
##     class counts:    25    18    11     2     0
##    probabilities: 0.446 0.321 0.196 0.036 0.000 
##   left son=3046 (31 obs) right son=3047 (25 obs)
##   Primary splits:
##       age               < 76.5   to the right, improve=2.6201380, (0 missing)
##       reimbursement2008 < 1225   to the right, improve=1.6819490, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.7819029, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.4322883, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.3928571, (0 missing)
##   Surrogate splits:
##       heart.failure     < 0.5    to the left,  agree=0.714, adj=0.36, (0 split)
##       reimbursement2008 < 1235   to the left,  agree=0.625, adj=0.16, (0 split)
##       kidney            < 0.5    to the left,  agree=0.571, adj=0.04, (0 split)
## 
## Node number 1536: 47 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.2340426  P(node) =0.00235
##     class counts:    36     3     8     0     0
##    probabilities: 0.766 0.064 0.170 0.000 0.000 
##   left son=3072 (40 obs) right son=3073 (7 obs)
##   Primary splits:
##       reimbursement2008 < 1655   to the right, improve=2.2937690, (0 missing)
##       age               < 74.5   to the right, improve=0.9731469, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.5429287, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2009119, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.2009119, (0 missing)
## 
## Node number 1537: 241 observations
##   predicted class=B1  expected loss=0.2821577  P(node) =0.01205
##     class counts:   173    40    20     8     0
##    probabilities: 0.718 0.166 0.083 0.033 0.000 
## 
## Node number 1538: 92 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3369565  P(node) =0.0046
##     class counts:    61    22     7     1     1
##    probabilities: 0.663 0.239 0.076 0.011 0.011 
##   left son=3076 (23 obs) right son=3077 (69 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=0.8695652, (0 missing)
##       reimbursement2008 < 2050   to the right, improve=0.8034579, (0 missing)
##       age               < 48.5   to the right, improve=0.5224638, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2776586, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.2576490, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2545   to the right, agree=0.783, adj=0.13, (0 split)
## 
## Node number 1539: 15 observations
##   predicted class=B1  expected loss=0.6  P(node) =0.00075
##     class counts:     6     5     4     0     0
##    probabilities: 0.400 0.333 0.267 0.000 0.000 
## 
## Node number 1542: 72 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.4027778  P(node) =0.0036
##     class counts:    43    21     6     2     0
##    probabilities: 0.597 0.292 0.083 0.028 0.000 
##   left son=3084 (58 obs) right son=3085 (14 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=1.1709090, (0 missing)
##       reimbursement2008 < 2415   to the left,  improve=1.1055560, (0 missing)
##       age               < 77.5   to the right, improve=0.5181735, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2448002, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.1190754, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2535   to the left,  agree=0.833, adj=0.143, (0 split)
## 
## Node number 1543: 28 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.6071429  P(node) =0.0014
##     class counts:    11     7     5     5     0
##    probabilities: 0.393 0.250 0.179 0.179 0.000 
##   left son=3086 (7 obs) right son=3087 (21 obs)
##   Primary splits:
##       arthritis         < 0.5    to the right, improve=1.3809520, (0 missing)
##       reimbursement2008 < 2070   to the left,  improve=1.1172160, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8539683, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.6925647, (0 missing)
##       age               < 84.5   to the right, improve=0.4345238, (0 missing)
##   Surrogate splits:
##       age < 82.5   to the left,  agree=0.786, adj=0.143, (0 split)
## 
## Node number 1556: 41 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.4146341  P(node) =0.00205
##     class counts:    24    17     0     0     0
##    probabilities: 0.585 0.415 0.000 0.000 0.000 
##   left son=3112 (30 obs) right son=3113 (11 obs)
##   Primary splits:
##       reimbursement2008 < 2765   to the right, improve=1.4781970, (0 missing)
##       age               < 77.5   to the left,  improve=1.4649390, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.4224390, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.5474390, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4579946, (0 missing)
## 
## Node number 1557: 25 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.4  P(node) =0.00125
##     class counts:    15     6     3     0     1
##    probabilities: 0.600 0.240 0.120 0.000 0.040 
##   left son=3114 (18 obs) right son=3115 (7 obs)
##   Primary splits:
##       reimbursement2008 < 3090   to the left,  improve=2.2711110, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=2.0933330, (0 missing)
##       age               < 89.5   to the left,  improve=0.4139683, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.3405556, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.88, adj=0.571, (0 split)
##       diabetes   < 0.5    to the left,  agree=0.80, adj=0.286, (0 split)
##       age        < 93.5   to the left,  agree=0.76, adj=0.143, (0 split)
## 
## Node number 1580: 26 observations
##   predicted class=B1  expected loss=0.3461538  P(node) =0.0013
##     class counts:    17     7     1     0     1
##    probabilities: 0.654 0.269 0.038 0.000 0.038 
## 
## Node number 1581: 24 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.5833333  P(node) =0.0012
##     class counts:    10     9     1     4     0
##    probabilities: 0.417 0.375 0.042 0.167 0.000 
##   left son=3162 (17 obs) right son=3163 (7 obs)
##   Primary splits:
##       age               < 68.5   to the left,  improve=1.2794120, (0 missing)
##       reimbursement2008 < 1855   to the right, improve=1.1785710, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4054622, (0 missing)
## 
## Node number 1590: 113 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5486726  P(node) =0.00565
##     class counts:    51    37    21     3     1
##    probabilities: 0.451 0.327 0.186 0.027 0.009 
##   left son=3180 (8 obs) right son=3181 (105 obs)
##   Primary splits:
##       reimbursement2008 < 3055   to the right, improve=2.8499160, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.9081570, (0 missing)
##       arthritis         < 0.5    to the right, improve=1.0615610, (0 missing)
##       age               < 75.5   to the right, improve=1.0498240, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7734827, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the right, agree=0.991, adj=0.875, (0 split)
## 
## Node number 1591: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     1     5     2     0     0
##    probabilities: 0.125 0.625 0.250 0.000 0.000 
## 
## Node number 1666: 86 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.3604651  P(node) =0.0043
##     class counts:    55    19     7     4     1
##    probabilities: 0.640 0.221 0.081 0.047 0.012 
##   left son=3332 (70 obs) right son=3333 (16 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=2.3426080, (0 missing)
##       age               < 91.5   to the right, improve=1.6553370, (0 missing)
##       copd              < 0.5    to the left,  improve=1.0437260, (0 missing)
##       reimbursement2008 < 2295   to the left,  improve=1.0350680, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4926252, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1585   to the right, agree=0.849, adj=0.187, (0 split)
## 
## Node number 1667: 58 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.5  P(node) =0.0029
##     class counts:    29    24     3     2     0
##    probabilities: 0.500 0.414 0.052 0.034 0.000 
##   left son=3334 (8 obs) right son=3335 (50 obs)
##   Primary splits:
##       age               < 75.5   to the left,  improve=1.4148280, (0 missing)
##       reimbursement2008 < 2375   to the left,  improve=0.6389452, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3897888, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.3122694, (0 missing)
##       copd              < 0.5    to the left,  improve=0.2848276, (0 missing)
## 
## Node number 1670: 63 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.5079365  P(node) =0.00315
##     class counts:    31    27     4     0     1
##    probabilities: 0.492 0.429 0.063 0.000 0.016 
##   left son=3340 (33 obs) right son=3341 (30 obs)
##   Primary splits:
##       reimbursement2008 < 2015   to the left,  improve=1.6441560, (0 missing)
##       age               < 87.5   to the left,  improve=1.0505420, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5047619, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3234222, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.1904762, (0 missing)
##   Surrogate splits:
##       age           < 84.5   to the left,  agree=0.651, adj=0.267, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.619, adj=0.200, (0 split)
##       osteoporosis  < 0.5    to the left,  agree=0.603, adj=0.167, (0 split)
##       kidney        < 0.5    to the left,  agree=0.556, adj=0.067, (0 split)
## 
## Node number 1671: 25 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.52  P(node) =0.00125
##     class counts:    12     6     2     5     0
##    probabilities: 0.480 0.240 0.080 0.200 0.000 
##   left son=3342 (10 obs) right son=3343 (15 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=2.8400000, (0 missing)
##       age               < 83     to the left,  improve=1.6400000, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.2893510, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.2400000, (0 missing)
##       reimbursement2008 < 2250   to the right, improve=0.3964103, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1705   to the left,  agree=0.72, adj=0.3, (0 split)
## 
## Node number 1672: 218 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.3899083  P(node) =0.0109
##     class counts:   133    56    18    10     1
##    probabilities: 0.610 0.257 0.083 0.046 0.005 
##   left son=3344 (211 obs) right son=3345 (7 obs)
##   Primary splits:
##       reimbursement2008 < 2485   to the left,  improve=2.3387790, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.3542280, (0 missing)
##       age               < 65.5   to the left,  improve=1.2410730, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3575472, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3120983, (0 missing)
## 
## Node number 1673: 10 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0005
##     class counts:     2     5     2     1     0
##    probabilities: 0.200 0.500 0.200 0.100 0.000 
## 
## Node number 1674: 26 observations,    complexity param=0.000380286
##   predicted class=B2  expected loss=0.6153846  P(node) =0.0013
##     class counts:     9    10     3     4     0
##    probabilities: 0.346 0.385 0.115 0.154 0.000 
##   left son=3348 (18 obs) right son=3349 (8 obs)
##   Primary splits:
##       age               < 54.5   to the right, improve=1.24359000, (0 missing)
##       reimbursement2008 < 1790   to the right, improve=1.21978000, (0 missing)
##       copd              < 0.5    to the left,  improve=0.92692310, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.88247860, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.04055944, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1620   to the right, agree=0.769, adj=0.25, (0 split)
## 
## Node number 1675: 7 observations
##   predicted class=B3  expected loss=0.2857143  P(node) =0.00035
##     class counts:     0     2     5     0     0
##    probabilities: 0.000 0.286 0.714 0.000 0.000 
## 
## Node number 1676: 115 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.5826087  P(node) =0.00575
##     class counts:    48    46    11     8     2
##    probabilities: 0.417 0.400 0.096 0.070 0.017 
##   left son=3352 (98 obs) right son=3353 (17 obs)
##   Primary splits:
##       age               < 55.5   to the right, improve=1.4583540, (0 missing)
##       reimbursement2008 < 2165   to the left,  improve=1.1979300, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.7250725, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7110961, (0 missing)
##       kidney            < 0.5    to the right, improve=0.5440382, (0 missing)
## 
## Node number 1677: 31 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.516129  P(node) =0.00155
##     class counts:     8    15     8     0     0
##    probabilities: 0.258 0.484 0.258 0.000 0.000 
##   left son=3354 (23 obs) right son=3355 (8 obs)
##   Primary splits:
##       age               < 62     to the right, improve=1.4824680, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.0802950, (0 missing)
##       reimbursement2008 < 2375   to the right, improve=0.9813243, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.4108830, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.3776091, (0 missing)
## 
## Node number 1678: 11 observations
##   predicted class=B1  expected loss=0.4545455  P(node) =0.00055
##     class counts:     6     4     1     0     0
##    probabilities: 0.545 0.364 0.091 0.000 0.000 
## 
## Node number 1679: 25 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.64  P(node) =0.00125
##     class counts:     9     3     9     3     1
##    probabilities: 0.360 0.120 0.360 0.120 0.040 
##   left son=3358 (8 obs) right son=3359 (17 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=1.0982350, (0 missing)
##       reimbursement2008 < 1975   to the right, improve=1.0805130, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.8988889, (0 missing)
##       age               < 62     to the right, improve=0.7600000, (0 missing)
##       kidney            < 0.5    to the right, improve=0.3850000, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1680   to the left,  agree=0.76, adj=0.250, (0 split)
##       arthritis         < 0.5    to the right, agree=0.72, adj=0.125, (0 split)
## 
## Node number 1712: 62 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.3225806  P(node) =0.0031
##     class counts:    42    11     4     4     1
##    probabilities: 0.677 0.177 0.065 0.065 0.016 
##   left son=3424 (28 obs) right son=3425 (34 obs)
##   Primary splits:
##       heart.failure < 0.5    to the right, improve=1.6485500, (0 missing)
##       arthritis     < 0.5    to the left,  improve=0.7549923, (0 missing)
##       diabetes      < 0.5    to the left,  improve=0.7121352, (0 missing)
##       age           < 65.5   to the right, improve=0.6478495, (0 missing)
##       kidney        < 0.5    to the left,  improve=0.6010580, (0 missing)
##   Surrogate splits:
##       age               < 64.5   to the left,  agree=0.629, adj=0.179, (0 split)
##       reimbursement2008 < 1640   to the left,  agree=0.629, adj=0.179, (0 split)
##       arthritis         < 0.5    to the right, agree=0.581, adj=0.071, (0 split)
##       osteoporosis      < 0.5    to the right, agree=0.581, adj=0.071, (0 split)
## 
## Node number 1713: 14 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0007
##     class counts:     6     7     0     1     0
##    probabilities: 0.429 0.500 0.000 0.071 0.000 
## 
## Node number 1714: 54 observations,    complexity param=0.0004563432
##   predicted class=B1  expected loss=0.6111111  P(node) =0.0027
##     class counts:    21    17    12     4     0
##    probabilities: 0.389 0.315 0.222 0.074 0.000 
##   left son=3428 (25 obs) right son=3429 (29 obs)
##   Primary splits:
##       reimbursement2008 < 2305   to the right, improve=1.9598980, (0 missing)
##       kidney            < 0.5    to the right, improve=0.8518519, (0 missing)
##       age               < 47.5   to the left,  improve=0.7033011, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6296296, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.4470899, (0 missing)
##   Surrogate splits:
##       age          < 67.5   to the left,  agree=0.593, adj=0.12, (0 split)
##       kidney       < 0.5    to the right, agree=0.593, adj=0.12, (0 split)
##       osteoporosis < 0.5    to the left,  agree=0.574, adj=0.08, (0 split)
##       copd         < 0.5    to the right, agree=0.556, adj=0.04, (0 split)
##       diabetes     < 0.5    to the left,  agree=0.556, adj=0.04, (0 split)
## 
## Node number 1715: 32 observations
##   predicted class=B2  expected loss=0.4375  P(node) =0.0016
##     class counts:     7    18     4     3     0
##    probabilities: 0.219 0.562 0.125 0.094 0.000 
## 
## Node number 1716: 8 observations
##   predicted class=B1  expected loss=0.375  P(node) =0.0004
##     class counts:     5     2     1     0     0
##    probabilities: 0.625 0.250 0.125 0.000 0.000 
## 
## Node number 1717: 109 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.4678899  P(node) =0.00545
##     class counts:    34    58    16     1     0
##    probabilities: 0.312 0.532 0.147 0.009 0.000 
##   left son=3434 (10 obs) right son=3435 (99 obs)
##   Primary splits:
##       reimbursement2008 < 2375   to the right, improve=1.1662310, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.6716092, (0 missing)
##       age               < 77.5   to the right, improve=0.6449413, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.4027486, (0 missing)
##       copd              < 0.5    to the right, improve=0.3923570, (0 missing)
## 
## Node number 1730: 37 observations
##   predicted class=B1  expected loss=0.4054054  P(node) =0.00185
##     class counts:    22    10     3     2     0
##    probabilities: 0.595 0.270 0.081 0.054 0.000 
## 
## Node number 1731: 10 observations
##   predicted class=B2  expected loss=0.4  P(node) =0.0005
##     class counts:     4     6     0     0     0
##    probabilities: 0.400 0.600 0.000 0.000 0.000 
## 
## Node number 1732: 23 observations
##   predicted class=B1  expected loss=0.173913  P(node) =0.00115
##     class counts:    19     2     2     0     0
##    probabilities: 0.826 0.087 0.087 0.000 0.000 
## 
## Node number 1733: 69 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4492754  P(node) =0.00345
##     class counts:    38    19     8     4     0
##    probabilities: 0.551 0.275 0.116 0.058 0.000 
##   left son=3466 (14 obs) right son=3467 (55 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the right, improve=1.5175230, (0 missing)
##       age               < 83.5   to the left,  improve=1.3893230, (0 missing)
##       copd              < 0.5    to the left,  improve=1.2426350, (0 missing)
##       reimbursement2008 < 2575   to the right, improve=0.9229627, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.3642763, (0 missing)
## 
## Node number 1734: 104 observations,    complexity param=0.0002662002
##   predicted class=B1  expected loss=0.5192308  P(node) =0.0052
##     class counts:    50    29    19     4     2
##    probabilities: 0.481 0.279 0.183 0.038 0.019 
##   left son=3468 (58 obs) right son=3469 (46 obs)
##   Primary splits:
##       age               < 79.5   to the left,  improve=2.1095890, (0 missing)
##       reimbursement2008 < 2985   to the right, improve=0.9038462, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7115385, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.6589459, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.5448718, (0 missing)
##   Surrogate splits:
##       depression < 0.5    to the left,  agree=0.577, adj=0.043, (0 split)
## 
## Node number 1735: 17 observations
##   predicted class=B2  expected loss=0.4117647  P(node) =0.00085
##     class counts:     3    10     3     1     0
##    probabilities: 0.176 0.588 0.176 0.059 0.000 
## 
## Node number 1744: 8 observations
##   predicted class=B1  expected loss=0.125  P(node) =0.0004
##     class counts:     7     1     0     0     0
##    probabilities: 0.875 0.125 0.000 0.000 0.000 
## 
## Node number 1745: 125 observations,    complexity param=0.0006084576
##   predicted class=B1  expected loss=0.552  P(node) =0.00625
##     class counts:    56    47    11    11     0
##    probabilities: 0.448 0.376 0.088 0.088 0.000 
##   left son=3490 (67 obs) right son=3491 (58 obs)
##   Primary splits:
##       reimbursement2008 < 2925   to the left,  improve=2.8552090, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=1.9365760, (0 missing)
##       age               < 69.5   to the right, improve=1.3716470, (0 missing)
##       depression        < 0.5    to the left,  improve=1.2843600, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.7595364, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.920, adj=0.828, (0 split)
##       age        < 68.5   to the right, agree=0.560, adj=0.052, (0 split)
##       cancer     < 0.5    to the left,  agree=0.544, adj=0.017, (0 split)
##       depression < 0.5    to the left,  agree=0.544, adj=0.017, (0 split)
## 
## Node number 1750: 10 observations
##   predicted class=B2  expected loss=0.3  P(node) =0.0005
##     class counts:     1     7     1     1     0
##    probabilities: 0.100 0.700 0.100 0.100 0.000 
## 
## Node number 1751: 46 observations,    complexity param=0.0003549336
##   predicted class=B2  expected loss=0.6956522  P(node) =0.0023
##     class counts:    12    14    13     7     0
##    probabilities: 0.261 0.304 0.283 0.152 0.000 
##   left son=3502 (39 obs) right son=3503 (7 obs)
##   Primary splits:
##       reimbursement2008 < 2845   to the right, improve=1.2541810, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7267081, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=0.6921773, (0 missing)
##       age               < 79.5   to the left,  improve=0.6284938, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6278986, (0 missing)
## 
## Node number 1760: 104 observations,    complexity param=0.0002788764
##   predicted class=B2  expected loss=0.5480769  P(node) =0.0052
##     class counts:    38    47    14     4     1
##    probabilities: 0.365 0.452 0.135 0.038 0.010 
##   left son=3520 (40 obs) right son=3521 (64 obs)
##   Primary splits:
##       reimbursement2008 < 2785   to the right, improve=0.8831731, (0 missing)
##       age               < 44.5   to the right, improve=0.5618273, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4772990, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.4681073, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4366792, (0 missing)
##   Surrogate splits:
##       age < 66.5   to the left,  agree=0.673, adj=0.15, (0 split)
## 
## Node number 1761: 38 observations,    complexity param=0.0002788764
##   predicted class=B2  expected loss=0.6315789  P(node) =0.0019
##     class counts:    11    14    13     0     0
##    probabilities: 0.289 0.368 0.342 0.000 0.000 
##   left son=3522 (12 obs) right son=3523 (26 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the right, improve=2.018219, (0 missing)
##       copd              < 0.5    to the left,  improve=1.710526, (0 missing)
##       reimbursement2008 < 2585   to the right, improve=1.660526, (0 missing)
##       age               < 67     to the left,  improve=1.530526, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.453383, (0 missing)
##   Surrogate splits:
##       age               < 49     to the left,  agree=0.789, adj=0.333, (0 split)
##       depression        < 0.5    to the right, agree=0.711, adj=0.083, (0 split)
##       reimbursement2008 < 2535   to the left,  agree=0.711, adj=0.083, (0 split)
## 
## Node number 1776: 11 observations
##   predicted class=B2  expected loss=0.3636364  P(node) =0.00055
##     class counts:     3     7     1     0     0
##    probabilities: 0.273 0.636 0.091 0.000 0.000 
## 
## Node number 1777: 29 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.5172414  P(node) =0.00145
##     class counts:    14     9     4     1     1
##    probabilities: 0.483 0.310 0.138 0.034 0.034 
##   left son=3554 (11 obs) right son=3555 (18 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=2.6659700, (0 missing)
##       age               < 70.5   to the left,  improve=1.7117970, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.7085386, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.6760711, (0 missing)
##       reimbursement2008 < 3195   to the right, improve=0.4333554, (0 missing)
##   Surrogate splits:
##       depression        < 0.5    to the left,  agree=0.69, adj=0.182, (0 split)
##       reimbursement2008 < 3105   to the left,  agree=0.69, adj=0.182, (0 split)
## 
## Node number 1794: 64 observations
##   predicted class=B1  expected loss=0.265625  P(node) =0.0032
##     class counts:    47    10     4     3     0
##    probabilities: 0.734 0.156 0.062 0.047 0.000 
## 
## Node number 1795: 30 observations,    complexity param=0.0001014096
##   predicted class=B1  expected loss=0.4666667  P(node) =0.0015
##     class counts:    16    10     3     1     0
##    probabilities: 0.533 0.333 0.100 0.033 0.000 
##   left son=3590 (23 obs) right son=3591 (7 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=1.1043480, (0 missing)
##       age               < 78.5   to the left,  improve=0.6035714, (0 missing)
##       reimbursement2008 < 4575   to the right, improve=0.2593301, (0 missing)
##       kidney            < 0.5    to the right, improve=0.1863636, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 7295   to the left,  agree=0.833, adj=0.286, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.833, adj=0.286, (0 split)
## 
## Node number 1796: 22 observations
##   predicted class=B1  expected loss=0.1363636  P(node) =0.0011
##     class counts:    19     2     1     0     0
##    probabilities: 0.864 0.091 0.045 0.000 0.000 
## 
## Node number 1797: 67 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.4328358  P(node) =0.00335
##     class counts:    38    19     6     3     1
##    probabilities: 0.567 0.284 0.090 0.045 0.015 
##   left son=3594 (56 obs) right son=3595 (11 obs)
##   Primary splits:
##       reimbursement2008 < 10695  to the right, improve=1.6978100, (0 missing)
##       age               < 79.5   to the left,  improve=1.5082190, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.4828650, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.8686780, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6091704, (0 missing)
##   Surrogate splits:
##       age < 51.5   to the right, agree=0.851, adj=0.091, (0 split)
## 
## Node number 1798: 105 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.4380952  P(node) =0.00525
##     class counts:    59    27    17     2     0
##    probabilities: 0.562 0.257 0.162 0.019 0.000 
##   left son=3596 (8 obs) right son=3597 (97 obs)
##   Primary splits:
##       age               < 88.5   to the right, improve=1.2302650, (0 missing)
##       reimbursement2008 < 5125   to the right, improve=1.1629710, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8149030, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.6619048, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.3031746, (0 missing)
## 
## Node number 1799: 16 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0008
##     class counts:     2     8     4     1     1
##    probabilities: 0.125 0.500 0.250 0.062 0.062 
## 
## Node number 1804: 26 observations
##   predicted class=B1  expected loss=0.3461538  P(node) =0.0013
##     class counts:    17     7     2     0     0
##    probabilities: 0.654 0.269 0.077 0.000 0.000 
## 
## Node number 1805: 34 observations,    complexity param=0.0003549336
##   predicted class=B2  expected loss=0.5294118  P(node) =0.0017
##     class counts:    13    16     3     2     0
##    probabilities: 0.382 0.471 0.088 0.059 0.000 
##   left son=3610 (22 obs) right son=3611 (12 obs)
##   Primary splits:
##       age               < 83.5   to the left,  improve=1.2843140, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5294118, (0 missing)
##       reimbursement2008 < 8165   to the right, improve=0.4298164, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.4298164, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.3587538, (0 missing)
##   Surrogate splits:
##       kidney            < 0.5    to the left,  agree=0.735, adj=0.250, (0 split)
##       reimbursement2008 < 9210   to the left,  agree=0.735, adj=0.250, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.676, adj=0.083, (0 split)
## 
## Node number 1822: 22 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5  P(node) =0.0011
##     class counts:     7    11     3     1     0
##    probabilities: 0.318 0.500 0.136 0.045 0.000 
##   left son=3644 (7 obs) right son=3645 (15 obs)
##   Primary splits:
##       reimbursement2008 < 14605  to the left,  improve=1.8372290, (0 missing)
##       copd              < 0.5    to the right, improve=0.6045066, (0 missing)
##       age               < 83.5   to the left,  improve=0.5454545, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4658009, (0 missing)
##       bucket2008        < 3.5    to the right, improve=0.4181818, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the left,  agree=0.773, adj=0.286, (0 split)
##       age        < 77     to the left,  agree=0.727, adj=0.143, (0 split)
## 
## Node number 1823: 32 observations,    complexity param=0.0003549336
##   predicted class=B3  expected loss=0.59375  P(node) =0.0016
##     class counts:    11     7    13     1     0
##    probabilities: 0.344 0.219 0.406 0.031 0.000 
##   left son=3646 (9 obs) right son=3647 (23 obs)
##   Primary splits:
##       copd              < 0.5    to the right, improve=1.4619570, (0 missing)
##       reimbursement2008 < 7995   to the left,  improve=1.1931820, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.1931820, (0 missing)
##       age               < 77.5   to the right, improve=0.7692857, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.6765873, (0 missing)
##   Surrogate splits:
##       kidney < 0.5    to the right, agree=0.812, adj=0.333, (0 split)
##       stroke < 0.5    to the right, agree=0.812, adj=0.333, (0 split)
## 
## Node number 1828: 18 observations
##   predicted class=B1  expected loss=0.3888889  P(node) =0.0009
##     class counts:    11     3     0     4     0
##    probabilities: 0.611 0.167 0.000 0.222 0.000 
## 
## Node number 1829: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     2     4     0     1     0
##    probabilities: 0.286 0.571 0.000 0.143 0.000 
## 
## Node number 1872: 11 observations
##   predicted class=B2  expected loss=0.4545455  P(node) =0.00055
##     class counts:     5     6     0     0     0
##    probabilities: 0.455 0.545 0.000 0.000 0.000 
## 
## Node number 1873: 16 observations
##   predicted class=B1  expected loss=0.3125  P(node) =0.0008
##     class counts:    11     2     2     1     0
##    probabilities: 0.688 0.125 0.125 0.062 0.000 
## 
## Node number 1874: 7 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.00035
##     class counts:     4     2     1     0     0
##    probabilities: 0.571 0.286 0.143 0.000 0.000 
## 
## Node number 1875: 38 observations,    complexity param=7.60572e-05
##   predicted class=B2  expected loss=0.3684211  P(node) =0.0019
##     class counts:     8    24     4     2     0
##    probabilities: 0.211 0.632 0.105 0.053 0.000 
##   left son=3750 (13 obs) right son=3751 (25 obs)
##   Primary splits:
##       reimbursement2008 < 4175   to the left,  improve=1.2469640, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3250655, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.3030075, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2482456, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.2387218, (0 missing)
##   Surrogate splits:
##       age          < 58.5   to the left,  agree=0.711, adj=0.154, (0 split)
##       osteoporosis < 0.5    to the right, agree=0.711, adj=0.154, (0 split)
## 
## Node number 1878: 13 observations
##   predicted class=B2  expected loss=0.3076923  P(node) =0.00065
##     class counts:     2     9     1     1     0
##    probabilities: 0.154 0.692 0.077 0.077 0.000 
## 
## Node number 1879: 39 observations,    complexity param=0.0003549336
##   predicted class=B3  expected loss=0.6410256  P(node) =0.00195
##     class counts:     9    13    14     3     0
##    probabilities: 0.231 0.333 0.359 0.077 0.000 
##   left son=3758 (25 obs) right son=3759 (14 obs)
##   Primary splits:
##       reimbursement2008 < 5860   to the right, improve=2.5504760, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.1111110, (0 missing)
##       age               < 69.5   to the right, improve=1.0712640, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.7000000, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.6969697, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.795, adj=0.429, (0 split)
##       age        < 68.5   to the right, agree=0.769, adj=0.357, (0 split)
## 
## Node number 1882: 26 observations
##   predicted class=B1  expected loss=0.5769231  P(node) =0.0013
##     class counts:    11     5     5     5     0
##    probabilities: 0.423 0.192 0.192 0.192 0.000 
## 
## Node number 1883: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     1     2     4     0     0
##    probabilities: 0.143 0.286 0.571 0.000 0.000 
## 
## Node number 1912: 30 observations,    complexity param=0.000253524
##   predicted class=B1  expected loss=0.6333333  P(node) =0.0015
##     class counts:    11    11     5     3     0
##    probabilities: 0.367 0.367 0.167 0.100 0.000 
##   left son=3824 (15 obs) right son=3825 (15 obs)
##   Primary splits:
##       age               < 68.5   to the right, improve=1.4666670, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.0009570, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9900452, (0 missing)
##       reimbursement2008 < 7610   to the right, improve=0.7130435, (0 missing)
##       kidney            < 0.5    to the right, improve=0.5222222, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 6645   to the left,  agree=0.667, adj=0.333, (0 split)
##       alzheimers        < 0.5    to the right, agree=0.600, adj=0.200, (0 split)
##       arthritis         < 0.5    to the left,  agree=0.533, adj=0.067, (0 split)
##       cancer            < 0.5    to the right, agree=0.533, adj=0.067, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.533, adj=0.067, (0 split)
## 
## Node number 1913: 11 observations
##   predicted class=B2  expected loss=0.5454545  P(node) =0.00055
##     class counts:     0     5     5     1     0
##    probabilities: 0.000 0.455 0.455 0.091 0.000 
## 
## Node number 1914: 31 observations
##   predicted class=B2  expected loss=0.4193548  P(node) =0.00155
##     class counts:     3    18     8     2     0
##    probabilities: 0.097 0.581 0.258 0.065 0.000 
## 
## Node number 1915: 7 observations
##   predicted class=B3  expected loss=0.2857143  P(node) =0.00035
##     class counts:     1     1     5     0     0
##    probabilities: 0.143 0.143 0.714 0.000 0.000 
## 
## Node number 1920: 32 observations,    complexity param=0.0003422574
##   predicted class=B1  expected loss=0.53125  P(node) =0.0016
##     class counts:    15    15     2     0     0
##    probabilities: 0.469 0.469 0.062 0.000 0.000 
##   left son=3840 (8 obs) right son=3841 (24 obs)
##   Primary splits:
##       age               < 57.5   to the left,  improve=0.8125000, (0 missing)
##       reimbursement2008 < 7940   to the right, improve=0.7690217, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.7690217, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.7034091, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3958333, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 8620   to the right, agree=0.812, adj=0.25, (0 split)
## 
## Node number 1921: 123 observations,    complexity param=0.0003422574
##   predicted class=B1  expected loss=0.495935  P(node) =0.00615
##     class counts:    62    32    26     3     0
##    probabilities: 0.504 0.260 0.211 0.024 0.000 
##   left son=3842 (19 obs) right son=3843 (104 obs)
##   Primary splits:
##       reimbursement2008 < 5150   to the right, improve=2.8759260, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.1396420, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6208037, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4917080, (0 missing)
##       age               < 59.5   to the left,  improve=0.4634146, (0 missing)
##   Surrogate splits:
##       age < 32.5   to the left,  agree=0.862, adj=0.105, (0 split)
## 
## Node number 1924: 31 observations,    complexity param=0.000507048
##   predicted class=B1  expected loss=0.6129032  P(node) =0.00155
##     class counts:    12    11     2     5     1
##    probabilities: 0.387 0.355 0.065 0.161 0.032 
##   left son=3848 (7 obs) right son=3849 (24 obs)
##   Primary splits:
##       age               < 67.5   to the right, improve=2.6862520, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9410138, (0 missing)
##       reimbursement2008 < 24480  to the left,  improve=0.8052995, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.6933948, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.4838710, (0 missing)
## 
## Node number 1925: 21 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.6666667  P(node) =0.00105
##     class counts:     4     5     7     5     0
##    probabilities: 0.190 0.238 0.333 0.238 0.000 
##   left son=3850 (13 obs) right son=3851 (8 obs)
##   Primary splits:
##       age               < 56.5   to the right, improve=0.8507326, (0 missing)
##       reimbursement2008 < 16675  to the left,  improve=0.6692641, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5815018, (0 missing)
##       bucket2008        < 3.5    to the right, improve=0.4853480, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4682540, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 16065  to the right, agree=0.667, adj=0.125, (0 split)
## 
## Node number 1926: 15 observations
##   predicted class=B1  expected loss=0.6  P(node) =0.00075
##     class counts:     6     3     5     1     0
##    probabilities: 0.400 0.200 0.333 0.067 0.000 
## 
## Node number 1927: 11 observations
##   predicted class=B3  expected loss=0.4545455  P(node) =0.00055
##     class counts:     2     0     6     3     0
##    probabilities: 0.182 0.000 0.545 0.273 0.000 
## 
## Node number 1928: 144 observations,    complexity param=0.0004563432
##   predicted class=B1  expected loss=0.5069444  P(node) =0.0072
##     class counts:    71    49    15     9     0
##    probabilities: 0.493 0.340 0.104 0.063 0.000 
##   left son=3856 (117 obs) right son=3857 (27 obs)
##   Primary splits:
##       age               < 73.5   to the right, improve=1.6075500, (0 missing)
##       reimbursement2008 < 5230   to the left,  improve=1.4092590, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6035354, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.5234020, (0 missing)
##       copd              < 0.5    to the right, improve=0.3870370, (0 missing)
## 
## Node number 1929: 26 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6538462  P(node) =0.0013
##     class counts:     7     9     8     1     1
##    probabilities: 0.269 0.346 0.308 0.038 0.038 
##   left son=3858 (7 obs) right son=3859 (19 obs)
##   Primary splits:
##       age               < 92.5   to the right, improve=1.7397340, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.4865380, (0 missing)
##       reimbursement2008 < 13275  to the left,  improve=1.1004270, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7115385, (0 missing)
##       copd              < 0.5    to the right, improve=0.6153846, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 5905   to the left,  agree=0.769, adj=0.143, (0 split)
## 
## Node number 1930: 28 observations,    complexity param=0.0006084576
##   predicted class=B1  expected loss=0.4642857  P(node) =0.0014
##     class counts:    15     9     1     2     1
##    probabilities: 0.536 0.321 0.036 0.071 0.036 
##   left son=3860 (17 obs) right son=3861 (11 obs)
##   Primary splits:
##       age               < 94.5   to the left,  improve=3.2207790, (0 missing)
##       reimbursement2008 < 15610  to the left,  improve=1.3333330, (0 missing)
##       copd              < 0.5    to the left,  improve=1.1488100, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.0091900, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7619048, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 18790  to the left,  agree=0.679, adj=0.182, (0 split)
##       bucket2008        < 3.5    to the left,  agree=0.679, adj=0.182, (0 split)
## 
## Node number 1931: 129 observations,    complexity param=0.0004056384
##   predicted class=B2  expected loss=0.5503876  P(node) =0.00645
##     class counts:    34    58    26    10     1
##    probabilities: 0.264 0.450 0.202 0.078 0.008 
##   left son=3862 (61 obs) right son=3863 (68 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=2.320337, (0 missing)
##       copd              < 0.5    to the left,  improve=1.845030, (0 missing)
##       reimbursement2008 < 6885   to the right, improve=1.627912, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.372989, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.116088, (0 missing)
##   Surrogate splits:
##       age               < 82.5   to the right, agree=0.597, adj=0.148, (0 split)
##       reimbursement2008 < 14610  to the left,  agree=0.566, adj=0.082, (0 split)
##       bucket2008        < 3.5    to the left,  agree=0.566, adj=0.082, (0 split)
##       ihd               < 0.5    to the left,  agree=0.535, adj=0.016, (0 split)
## 
## Node number 1932: 64 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.40625  P(node) =0.0032
##     class counts:    17    38     7     2     0
##    probabilities: 0.266 0.594 0.109 0.031 0.000 
##   left son=3864 (50 obs) right son=3865 (14 obs)
##   Primary splits:
##       reimbursement2008 < 4345   to the left,  improve=4.173750, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.653328, (0 missing)
##       age               < 72.5   to the left,  improve=1.548721, (0 missing)
##       depression        < 0.5    to the left,  improve=0.793750, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.494532, (0 missing)
## 
## Node number 1933: 10 observations
##   predicted class=B2  expected loss=0  P(node) =0.0005
##     class counts:     0    10     0     0     0
##    probabilities: 0.000 1.000 0.000 0.000 0.000 
## 
## Node number 1934: 9 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.00045
##     class counts:     6     1     2     0     0
##    probabilities: 0.667 0.111 0.222 0.000 0.000 
## 
## Node number 1935: 104 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.4903846  P(node) =0.0052
##     class counts:    28    53    18     5     0
##    probabilities: 0.269 0.510 0.173 0.048 0.000 
##   left son=3870 (37 obs) right son=3871 (67 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=1.7427860, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.3422740, (0 missing)
##       stroke            < 0.5    to the right, improve=1.1791950, (0 missing)
##       reimbursement2008 < 4030   to the left,  improve=1.0517090, (0 missing)
##       age               < 80.5   to the left,  improve=0.6396844, (0 missing)
##   Surrogate splits:
##       stroke < 0.5    to the right, agree=0.654, adj=0.027, (0 split)
## 
## Node number 1946: 49 observations,    complexity param=0.0005324004
##   predicted class=B1  expected loss=0.6734694  P(node) =0.00245
##     class counts:    16    13    16     4     0
##    probabilities: 0.327 0.265 0.327 0.082 0.000 
##   left son=3892 (16 obs) right son=3893 (33 obs)
##   Primary splits:
##       copd              < 0.5    to the right, improve=1.7300560, (0 missing)
##       reimbursement2008 < 5825   to the left,  improve=1.6040820, (0 missing)
##       age               < 67.5   to the right, improve=1.2805610, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.0381360, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8306573, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 25990  to the right, agree=0.755, adj=0.250, (0 split)
##       age               < 65.5   to the left,  agree=0.735, adj=0.188, (0 split)
##       bucket2008        < 3.5    to the right, agree=0.735, adj=0.188, (0 split)
## 
## Node number 1947: 63 observations,    complexity param=0.0005324004
##   predicted class=B2  expected loss=0.5873016  P(node) =0.00315
##     class counts:     8    26    22     7     0
##    probabilities: 0.127 0.413 0.349 0.111 0.000 
##   left son=3894 (33 obs) right son=3895 (30 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=2.2784990, (0 missing)
##       age               < 73.5   to the left,  improve=1.4389340, (0 missing)
##       reimbursement2008 < 14505  to the left,  improve=1.1107860, (0 missing)
##       copd              < 0.5    to the left,  improve=0.7714286, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6362229, (0 missing)
##   Surrogate splits:
##       alzheimers        < 0.5    to the left,  agree=0.651, adj=0.267, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.635, adj=0.233, (0 split)
##       reimbursement2008 < 13275  to the left,  agree=0.635, adj=0.233, (0 split)
##       copd              < 0.5    to the left,  agree=0.587, adj=0.133, (0 split)
##       stroke            < 0.5    to the left,  agree=0.587, adj=0.133, (0 split)
## 
## Node number 1968: 38 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5  P(node) =0.0019
##     class counts:    19    12     2     4     1
##    probabilities: 0.500 0.316 0.053 0.105 0.026 
##   left son=3936 (30 obs) right son=3937 (8 obs)
##   Primary splits:
##       age               < 67.5   to the right, improve=1.4745610, (0 missing)
##       reimbursement2008 < 14135  to the left,  improve=0.7888471, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5412281, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.5108359, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=0.3373819, (0 missing)
## 
## Node number 1969: 18 observations
##   predicted class=B2  expected loss=0.5555556  P(node) =0.0009
##     class counts:     2     8     4     2     2
##    probabilities: 0.111 0.444 0.222 0.111 0.111 
## 
## Node number 1970: 85 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5529412  P(node) =0.00425
##     class counts:    27    38    11     8     1
##    probabilities: 0.318 0.447 0.129 0.094 0.012 
##   left son=3940 (59 obs) right son=3941 (26 obs)
##   Primary splits:
##       age               < 80.5   to the left,  improve=1.2457550, (0 missing)
##       reimbursement2008 < 5820   to the left,  improve=1.0846660, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7174773, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5925134, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3022536, (0 missing)
## 
## Node number 1971: 42 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.452381  P(node) =0.0021
##     class counts:     4    23     6     9     0
##    probabilities: 0.095 0.548 0.143 0.214 0.000 
##   left son=3942 (32 obs) right son=3943 (10 obs)
##   Primary splits:
##       age               < 67.5   to the right, improve=2.2755950, (0 missing)
##       reimbursement2008 < 6595   to the right, improve=0.5809524, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.2880952, (0 missing)
##       copd              < 0.5    to the right, improve=0.2861722, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.1707875, (0 missing)
## 
## Node number 1972: 16 observations
##   predicted class=B1  expected loss=0.625  P(node) =0.0008
##     class counts:     6     6     4     0     0
##    probabilities: 0.375 0.375 0.250 0.000 0.000 
## 
## Node number 1973: 21 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5714286  P(node) =0.00105
##     class counts:     4     9     1     7     0
##    probabilities: 0.190 0.429 0.048 0.333 0.000 
##   left son=3946 (10 obs) right son=3947 (11 obs)
##   Primary splits:
##       age               < 87     to the right, improve=0.9454545, (0 missing)
##       copd              < 0.5    to the right, improve=0.9423077, (0 missing)
##       reimbursement2008 < 10955  to the right, improve=0.4545455, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.2307692, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.1923077, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4780   to the right, agree=0.667, adj=0.3, (0 split)
##       osteoporosis      < 0.5    to the right, agree=0.619, adj=0.2, (0 split)
##       cancer            < 0.5    to the right, agree=0.571, adj=0.1, (0 split)
##       copd              < 0.5    to the right, agree=0.571, adj=0.1, (0 split)
## 
## Node number 1974: 17 observations
##   predicted class=B2  expected loss=0.2352941  P(node) =0.00085
##     class counts:     1    13     2     1     0
##    probabilities: 0.059 0.765 0.118 0.059 0.000 
## 
## Node number 1975: 45 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4666667  P(node) =0.00225
##     class counts:     5    24    14     2     0
##    probabilities: 0.111 0.533 0.311 0.044 0.000 
##   left son=3950 (23 obs) right son=3951 (22 obs)
##   Primary splits:
##       reimbursement2008 < 5595   to the left,  improve=2.8877470, (0 missing)
##       age               < 70.5   to the left,  improve=0.7770751, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4450593, (0 missing)
##       copd              < 0.5    to the right, improve=0.2106952, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1447005, (0 missing)
##   Surrogate splits:
##       osteoporosis  < 0.5    to the right, agree=0.667, adj=0.318, (0 split)
##       age           < 70.5   to the left,  agree=0.622, adj=0.227, (0 split)
##       bucket2008    < 2.5    to the left,  agree=0.622, adj=0.227, (0 split)
##       copd          < 0.5    to the left,  agree=0.578, adj=0.136, (0 split)
##       heart.failure < 0.5    to the right, agree=0.578, adj=0.136, (0 split)
## 
## Node number 1978: 216 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5462963  P(node) =0.0108
##     class counts:    42    98    56    18     2
##    probabilities: 0.194 0.454 0.259 0.083 0.009 
##   left son=3956 (52 obs) right son=3957 (164 obs)
##   Primary splits:
##       reimbursement2008 < 15105  to the right, improve=1.4684180, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.4512310, (0 missing)
##       age               < 71.5   to the right, improve=1.0436270, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8503280, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7569892, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.926, adj=0.692, (0 split)
##       age        < 55.5   to the left,  agree=0.764, adj=0.019, (0 split)
## 
## Node number 1979: 9 observations
##   predicted class=B3  expected loss=0.5555556  P(node) =0.00045
##     class counts:     1     1     4     3     0
##    probabilities: 0.111 0.111 0.444 0.333 0.000 
## 
## Node number 1984: 43 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5813953  P(node) =0.00215
##     class counts:    18     9    12     2     2
##    probabilities: 0.419 0.209 0.279 0.047 0.047 
##   left son=3968 (11 obs) right son=3969 (32 obs)
##   Primary splits:
##       reimbursement2008 < 8495   to the left,  improve=2.1203750, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.3253000, (0 missing)
##       age               < 96.5   to the left,  improve=1.2164460, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9252995, (0 missing)
##       copd              < 0.5    to the right, improve=0.5070379, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.884, adj=0.545, (0 split)
## 
## Node number 1985: 24 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.625  P(node) =0.0012
##     class counts:     4     9     9     2     0
##    probabilities: 0.167 0.375 0.375 0.083 0.000 
##   left son=3970 (8 obs) right son=3971 (16 obs)
##   Primary splits:
##       reimbursement2008 < 9045   to the left,  improve=2.2916670, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8921911, (0 missing)
##       age               < 87.5   to the left,  improve=0.7722222, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.7722222, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.4166667, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.750, adj=0.250, (0 split)
##       age        < 89.5   to the right, agree=0.708, adj=0.125, (0 split)
## 
## Node number 1986: 11 observations
##   predicted class=B1  expected loss=0.4545455  P(node) =0.00055
##     class counts:     6     1     1     3     0
##    probabilities: 0.545 0.091 0.091 0.273 0.000 
## 
## Node number 1987: 268 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6231343  P(node) =0.0134
##     class counts:    60   101    49    50     8
##    probabilities: 0.224 0.377 0.183 0.187 0.030 
##   left son=3974 (177 obs) right son=3975 (91 obs)
##   Primary splits:
##       age               < 77.5   to the left,  improve=1.6839510, (0 missing)
##       reimbursement2008 < 14425  to the left,  improve=1.3251930, (0 missing)
##       stroke            < 0.5    to the right, improve=1.2532710, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.9809812, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9444366, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 13575  to the left,  agree=0.679, adj=0.055, (0 split)
## 
## Node number 1990: 235 observations,    complexity param=0.0003650745
##   predicted class=B2  expected loss=0.6042553  P(node) =0.01175
##     class counts:    45    93    59    32     6
##    probabilities: 0.191 0.396 0.251 0.136 0.026 
##   left son=3980 (210 obs) right son=3981 (25 obs)
##   Primary splits:
##       reimbursement2008 < 6170   to the left,  improve=2.3734140, (0 missing)
##       age               < 81.5   to the right, improve=1.4517590, (0 missing)
##       depression        < 0.5    to the right, improve=0.7995092, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.6947270, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6162007, (0 missing)
## 
## Node number 1991: 12 observations
##   predicted class=B3  expected loss=0.3333333  P(node) =0.0006
##     class counts:     2     2     8     0     0
##    probabilities: 0.167 0.167 0.667 0.000 0.000 
## 
## Node number 2004: 88 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.4318182  P(node) =0.0044
##     class counts:    16    50    14     7     1
##    probabilities: 0.182 0.568 0.159 0.080 0.011 
##   left son=4008 (19 obs) right son=4009 (69 obs)
##   Primary splits:
##       reimbursement2008 < 3725   to the left,  improve=1.1251130, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.9988702, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.7978634, (0 missing)
##       age               < 90.5   to the left,  improve=0.6812354, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.5300418, (0 missing)
## 
## Node number 2005: 19 observations
##   predicted class=B2  expected loss=0.2105263  P(node) =0.00095
##     class counts:     0    15     1     3     0
##    probabilities: 0.000 0.789 0.053 0.158 0.000 
## 
## Node number 2006: 16 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0008
##     class counts:     3     8     3     2     0
##    probabilities: 0.188 0.500 0.188 0.125 0.000 
## 
## Node number 2007: 9 observations
##   predicted class=B3  expected loss=0.5555556  P(node) =0.00045
##     class counts:     1     2     4     2     0
##    probabilities: 0.111 0.222 0.444 0.222 0.000 
## 
## Node number 2012: 35 observations,    complexity param=0.0002028192
##   predicted class=B3  expected loss=0.6571429  P(node) =0.00175
##     class counts:     7    11    12     5     0
##    probabilities: 0.200 0.314 0.343 0.143 0.000 
##   left son=4024 (13 obs) right son=4025 (22 obs)
##   Primary splits:
##       age               < 72.5   to the left,  improve=1.2093910, (0 missing)
##       reimbursement2008 < 6400   to the right, improve=0.9571429, (0 missing)
##       depression        < 0.5    to the right, improve=0.4095238, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.3340226, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1910973, (0 missing)
##   Surrogate splits:
##       stroke < 0.5    to the right, agree=0.657, adj=0.077, (0 split)
## 
## Node number 2013: 218 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5229358  P(node) =0.0109
##     class counts:    22   104    57    30     5
##    probabilities: 0.101 0.477 0.261 0.138 0.023 
##   left son=4026 (187 obs) right son=4027 (31 obs)
##   Primary splits:
##       reimbursement2008 < 7265   to the right, improve=1.4088950, (0 missing)
##       copd              < 0.5    to the left,  improve=1.3174740, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.2029980, (0 missing)
##       age               < 75.5   to the left,  improve=0.7552085, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.5102534, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.913, adj=0.387, (0 split)
## 
## Node number 2014: 22 observations
##   predicted class=B2  expected loss=0.2272727  P(node) =0.0011
##     class counts:     0    17     4     0     1
##    probabilities: 0.000 0.773 0.182 0.000 0.045 
## 
## Node number 2015: 10 observations
##   predicted class=B3  expected loss=0.6  P(node) =0.0005
##     class counts:     0     3     4     3     0
##    probabilities: 0.000 0.300 0.400 0.300 0.000 
## 
## Node number 2032: 67 observations,    complexity param=0.0004563432
##   predicted class=B1  expected loss=0.6716418  P(node) =0.00335
##     class counts:    22    12    17    16     0
##    probabilities: 0.328 0.179 0.254 0.239 0.000 
##   left son=4064 (59 obs) right son=4065 (8 obs)
##   Primary splits:
##       reimbursement2008 < 18390  to the right, improve=1.7171140, (0 missing)
##       stroke            < 0.5    to the right, improve=1.6606280, (0 missing)
##       cancer            < 0.5    to the right, improve=1.0990060, (0 missing)
##       age               < 80.5   to the left,  improve=0.9955676, (0 missing)
##       bucket2008        < 3.5    to the right, improve=0.8525373, (0 missing)
## 
## Node number 2033: 28 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.6071429  P(node) =0.0014
##     class counts:     5    11     3     9     0
##    probabilities: 0.179 0.393 0.107 0.321 0.000 
##   left son=4066 (9 obs) right son=4067 (19 obs)
##   Primary splits:
##       reimbursement2008 < 16540  to the left,  improve=2.1796160, (0 missing)
##       depression        < 0.5    to the left,  improve=1.2857140, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.9047619, (0 missing)
##       age               < 70.5   to the left,  improve=0.8158730, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3630952, (0 missing)
## 
## Node number 2034: 41 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5121951  P(node) =0.00205
##     class counts:     7    20     6     4     4
##    probabilities: 0.171 0.488 0.146 0.098 0.098 
##   left son=4068 (32 obs) right son=4069 (9 obs)
##   Primary splits:
##       age               < 83.5   to the left,  improve=2.1888550, (0 missing)
##       reimbursement2008 < 25405  to the right, improve=1.4735770, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9644375, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.8832995, (0 missing)
##       stroke            < 0.5    to the right, improve=0.7966955, (0 missing)
## 
## Node number 2035: 97 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6907216  P(node) =0.00485
##     class counts:    14    30    23    26     4
##    probabilities: 0.144 0.309 0.237 0.268 0.041 
##   left son=4070 (81 obs) right son=4071 (16 obs)
##   Primary splits:
##       reimbursement2008 < 21150  to the left,  improve=2.1982790, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.8385610, (0 missing)
##       age               < 58     to the right, improve=1.5250180, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.8794627, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7745519, (0 missing)
## 
## Node number 2036: 125 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.568  P(node) =0.00625
##     class counts:    17    54    32    16     6
##    probabilities: 0.136 0.432 0.256 0.128 0.048 
##   left son=4072 (36 obs) right son=4073 (89 obs)
##   Primary splits:
##       reimbursement2008 < 22510  to the right, improve=1.5030360, (0 missing)
##       age               < 71.5   to the left,  improve=1.4083000, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.0672150, (0 missing)
##       bucket2008        < 3.5    to the right, improve=1.0234450, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9386667, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.72, adj=0.028, (0 split)
## 
## Node number 2037: 15 observations
##   predicted class=B3  expected loss=0.6  P(node) =0.00075
##     class counts:     0     3     6     4     2
##    probabilities: 0.000 0.200 0.400 0.267 0.133 
## 
## Node number 2038: 13 observations
##   predicted class=B2  expected loss=0.6153846  P(node) =0.00065
##     class counts:     1     5     3     3     1
##    probabilities: 0.077 0.385 0.231 0.231 0.077 
## 
## Node number 2039: 10 observations
##   predicted class=B3  expected loss=0.1  P(node) =0.0005
##     class counts:     0     0     9     1     0
##    probabilities: 0.000 0.000 0.900 0.100 0.000 
## 
## Node number 2044: 47 observations,    complexity param=0.0002662002
##   predicted class=B2  expected loss=0.4680851  P(node) =0.00235
##     class counts:     3    25    10     6     3
##    probabilities: 0.064 0.532 0.213 0.128 0.064 
##   left son=4088 (30 obs) right son=4089 (17 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=3.2804340, (0 missing)
##       age               < 81.5   to the left,  improve=1.9668850, (0 missing)
##       reimbursement2008 < 31080  to the right, improve=1.4612460, (0 missing)
##       copd              < 0.5    to the right, improve=1.1322990, (0 missing)
##       depression        < 0.5    to the right, improve=0.8569045, (0 missing)
##   Surrogate splits:
##       age               < 85.5   to the left,  agree=0.702, adj=0.176, (0 split)
##       reimbursement2008 < 31580  to the left,  agree=0.660, adj=0.059, (0 split)
## 
## Node number 2045: 44 observations,    complexity param=0.0002662002
##   predicted class=B2  expected loss=0.5681818  P(node) =0.0022
##     class counts:     3    19     7    15     0
##    probabilities: 0.068 0.432 0.159 0.341 0.000 
##   left son=4090 (11 obs) right son=4091 (33 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=1.5454550, (0 missing)
##       age               < 55.5   to the left,  improve=1.5257990, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.3346510, (0 missing)
##       reimbursement2008 < 29895  to the right, improve=0.8874459, (0 missing)
##       stroke            < 0.5    to the right, improve=0.7160173, (0 missing)
##   Surrogate splits:
##       age < 55.5   to the left,  agree=0.773, adj=0.091, (0 split)
## 
## Node number 2046: 97 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5979381  P(node) =0.00485
##     class counts:     6    39    17    28     7
##    probabilities: 0.062 0.402 0.175 0.289 0.072 
##   left son=4092 (26 obs) right son=4093 (71 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=1.5049540, (0 missing)
##       reimbursement2008 < 37785  to the left,  improve=1.3125260, (0 missing)
##       age               < 79.5   to the left,  improve=1.1547350, (0 missing)
##       cancer            < 0.5    to the right, improve=1.1520240, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9743395, (0 missing)
##   Surrogate splits:
##       heart.failure < 0.5    to the left,  agree=0.753, adj=0.077, (0 split)
## 
## Node number 2047: 234 observations,    complexity param=0.000507048
##   predicted class=B4  expected loss=0.6709402  P(node) =0.0117
##     class counts:    18    65    63    77    11
##    probabilities: 0.077 0.278 0.269 0.329 0.047 
##   left son=4094 (180 obs) right son=4095 (54 obs)
##   Primary splits:
##       reimbursement2008 < 37290  to the right, improve=2.5176640, (0 missing)
##       bucket2008        < 4.5    to the right, improve=2.4693040, (0 missing)
##       age               < 36.5   to the left,  improve=0.9682593, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8197802, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.8182531, (0 missing)
## 
## Node number 2570: 277 observations
##   predicted class=B1  expected loss=0.1371841  P(node) =0.01385
##     class counts:   239    21    10     7     0
##    probabilities: 0.863 0.076 0.036 0.025 0.000 
## 
## Node number 2571: 430 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1837209  P(node) =0.0215
##     class counts:   351    47    26     4     2
##    probabilities: 0.816 0.109 0.060 0.009 0.005 
##   left son=5142 (398 obs) right son=5143 (32 obs)
##   Primary splits:
##       reimbursement2008 < 475    to the left,  improve=1.1570540, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.5902656, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4826179, (0 missing)
##       age               < 86.5   to the left,  improve=0.4570367, (0 missing)
##       kidney            < 0.5    to the right, improve=0.2437930, (0 missing)
## 
## Node number 2842: 60 observations
##   predicted class=B1  expected loss=0.2666667  P(node) =0.003
##     class counts:    44    12     3     1     0
##    probabilities: 0.733 0.200 0.050 0.017 0.000 
## 
## Node number 2843: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     3     4     0     0     0
##    probabilities: 0.429 0.571 0.000 0.000 0.000 
## 
## Node number 2882: 197 observations
##   predicted class=B1  expected loss=0.1928934  P(node) =0.00985
##     class counts:   159    18    13     7     0
##    probabilities: 0.807 0.091 0.066 0.036 0.000 
## 
## Node number 2883: 59 observations,    complexity param=5.07048e-05
##   predicted class=B1  expected loss=0.3389831  P(node) =0.00295
##     class counts:    39    10     8     2     0
##    probabilities: 0.661 0.169 0.136 0.034 0.000 
##   left son=5766 (51 obs) right son=5767 (8 obs)
##   Primary splits:
##       reimbursement2008 < 1115   to the right, improve=1.7797440, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.2458970, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9810446, (0 missing)
##       age               < 83.5   to the left,  improve=0.7705825, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.4388154, (0 missing)
## 
## Node number 2884: 109 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.2844037  P(node) =0.00545
##     class counts:    78    21     9     1     0
##    probabilities: 0.716 0.193 0.083 0.009 0.000 
##   left son=5768 (79 obs) right son=5769 (30 obs)
##   Primary splits:
##       age               < 77.5   to the right, improve=1.7532540, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.7212762, (0 missing)
##       reimbursement2008 < 1545   to the left,  improve=0.6234163, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.4323641, (0 missing)
##       kidney            < 0.5    to the right, improve=0.4275433, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1345   to the right, agree=0.752, adj=0.1, (0 split)
## 
## Node number 2885: 49 observations
##   predicted class=B1  expected loss=0.244898  P(node) =0.00245
##     class counts:    37     4     4     4     0
##    probabilities: 0.755 0.082 0.082 0.082 0.000 
## 
## Node number 2892: 32 observations
##   predicted class=B1  expected loss=0.1875  P(node) =0.0016
##     class counts:    26     4     1     1     0
##    probabilities: 0.813 0.125 0.031 0.031 0.000 
## 
## Node number 2893: 20 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.45  P(node) =0.001
##     class counts:    11     6     1     2     0
##    probabilities: 0.550 0.300 0.050 0.100 0.000 
##   left son=5786 (9 obs) right son=5787 (11 obs)
##   Primary splits:
##       reimbursement2008 < 1115   to the left,  improve=1.4757580, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.1500000, (0 missing)
##       age               < 54     to the right, improve=0.5666667, (0 missing)
##   Surrogate splits:
##       diabetes      < 0.5    to the left,  agree=0.75, adj=0.444, (0 split)
##       age           < 41     to the left,  agree=0.70, adj=0.333, (0 split)
##       depression    < 0.5    to the right, agree=0.60, adj=0.111, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.60, adj=0.111, (0 split)
## 
## Node number 2894: 15 observations
##   predicted class=B1  expected loss=0.2666667  P(node) =0.00075
##     class counts:    11     3     1     0     0
##    probabilities: 0.733 0.200 0.067 0.000 0.000 
## 
## Node number 2895: 20 observations,    complexity param=8.450799e-05
##   predicted class=B2  expected loss=0.45  P(node) =0.001
##     class counts:     9    11     0     0     0
##    probabilities: 0.450 0.550 0.000 0.000 0.000 
##   left son=5790 (11 obs) right son=5791 (9 obs)
##   Primary splits:
##       reimbursement2008 < 1275   to the right, improve=0.445454500, (0 missing)
##       age               < 64.5   to the left,  improve=0.100000000, (0 missing)
##       depression        < 0.5    to the left,  improve=0.001010101, (0 missing)
##   Surrogate splits:
##       age        < 46     to the right, agree=0.6, adj=0.111, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.6, adj=0.111, (0 split)
##       depression < 0.5    to the right, agree=0.6, adj=0.111, (0 split)
## 
## Node number 2948: 8 observations
##   predicted class=B1  expected loss=0  P(node) =0.0004
##     class counts:     8     0     0     0     0
##    probabilities: 1.000 0.000 0.000 0.000 0.000 
## 
## Node number 2949: 137 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.2992701  P(node) =0.00685
##     class counts:    96    25    13     3     0
##    probabilities: 0.701 0.182 0.095 0.022 0.000 
##   left son=5898 (10 obs) right son=5899 (127 obs)
##   Primary splits:
##       copd              < 0.5    to the right, improve=0.7930226, (0 missing)
##       reimbursement2008 < 875    to the left,  improve=0.5527217, (0 missing)
##       age               < 79.5   to the left,  improve=0.4583429, (0 missing)
##       depression        < 0.5    to the right, improve=0.4287322, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1222173, (0 missing)
## 
## Node number 2950: 8 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.0004
##     class counts:     6     1     0     1     0
##    probabilities: 0.750 0.125 0.000 0.125 0.000 
## 
## Node number 2951: 20 observations,    complexity param=6.519188e-05
##   predicted class=B2  expected loss=0.6  P(node) =0.001
##     class counts:     7     8     4     1     0
##    probabilities: 0.350 0.400 0.200 0.050 0.000 
##   left son=5902 (7 obs) right son=5903 (13 obs)
##   Primary splits:
##       age               < 66.5   to the left,  improve=0.3131868, (0 missing)
##       reimbursement2008 < 770    to the left,  improve=0.3131868, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 805    to the right, agree=0.85, adj=0.571, (0 split)
## 
## Node number 3026: 14 observations
##   predicted class=B1  expected loss=0.07142857  P(node) =0.0007
##     class counts:    13     1     0     0     0
##    probabilities: 0.929 0.071 0.000 0.000 0.000 
## 
## Node number 3027: 125 observations,    complexity param=6.084576e-05
##   predicted class=B1  expected loss=0.344  P(node) =0.00625
##     class counts:    82    30    12     0     1
##    probabilities: 0.656 0.240 0.096 0.000 0.008 
##   left son=6054 (10 obs) right son=6055 (115 obs)
##   Primary splits:
##       arthritis         < 0.5    to the right, improve=0.9610435, (0 missing)
##       kidney            < 0.5    to the right, improve=0.8457324, (0 missing)
##       age               < 73.5   to the right, improve=0.7907549, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6473119, (0 missing)
##       reimbursement2008 < 925    to the right, improve=0.5392281, (0 missing)
## 
## Node number 3028: 9 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.00045
##     class counts:     4     5     0     0     0
##    probabilities: 0.444 0.556 0.000 0.000 0.000 
## 
## Node number 3029: 59 observations
##   predicted class=B1  expected loss=0.3050847  P(node) =0.00295
##     class counts:    41     8     5     5     0
##    probabilities: 0.695 0.136 0.085 0.085 0.000 
## 
## Node number 3030: 20 observations
##   predicted class=B1  expected loss=0.45  P(node) =0.001
##     class counts:    11     7     1     1     0
##    probabilities: 0.550 0.350 0.050 0.050 0.000 
## 
## Node number 3031: 9 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.00045
##     class counts:     3     5     1     0     0
##    probabilities: 0.333 0.556 0.111 0.000 0.000 
## 
## Node number 3046: 31 observations
##   predicted class=B1  expected loss=0.4516129  P(node) =0.00155
##     class counts:    17     5     7     2     0
##    probabilities: 0.548 0.161 0.226 0.065 0.000 
## 
## Node number 3047: 25 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.48  P(node) =0.00125
##     class counts:     8    13     4     0     0
##    probabilities: 0.320 0.520 0.160 0.000 0.000 
##   left son=6094 (18 obs) right son=6095 (7 obs)
##   Primary splits:
##       reimbursement2008 < 1435   to the left,  improve=2.7225400, (0 missing)
##       age               < 74.5   to the left,  improve=0.3782353, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.3316667, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.2463492, (0 missing)
##   Surrogate splits:
##       age < 75.5   to the left,  agree=0.76, adj=0.143, (0 split)
## 
## Node number 3072: 40 observations
##   predicted class=B1  expected loss=0.175  P(node) =0.002
##     class counts:    33     3     4     0     0
##    probabilities: 0.825 0.075 0.100 0.000 0.000 
## 
## Node number 3073: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     3     0     4     0     0
##    probabilities: 0.429 0.000 0.571 0.000 0.000 
## 
## Node number 3076: 23 observations
##   predicted class=B1  expected loss=0.2173913  P(node) =0.00115
##     class counts:    18     3     1     1     0
##    probabilities: 0.783 0.130 0.043 0.043 0.000 
## 
## Node number 3077: 69 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3768116  P(node) =0.00345
##     class counts:    43    19     6     0     1
##    probabilities: 0.623 0.275 0.087 0.000 0.014 
##   left son=6154 (59 obs) right son=6155 (10 obs)
##   Primary splits:
##       reimbursement2008 < 2295   to the left,  improve=0.9161385, (0 missing)
##       age               < 47     to the right, improve=0.6125604, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.4294916, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2435600, (0 missing)
## 
## Node number 3084: 58 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.4137931  P(node) =0.0029
##     class counts:    34    20     4     0     0
##    probabilities: 0.586 0.345 0.069 0.000 0.000 
##   left son=6168 (49 obs) right son=6169 (9 obs)
##   Primary splits:
##       reimbursement2008 < 2415   to the left,  improve=0.73782160, (0 missing)
##       age               < 77.5   to the right, improve=0.37655170, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.12048330, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.03843207, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.01005232, (0 missing)
##   Surrogate splits:
##       copd < 0.5    to the left,  agree=0.879, adj=0.222, (0 split)
## 
## Node number 3085: 14 observations
##   predicted class=B1  expected loss=0.3571429  P(node) =0.0007
##     class counts:     9     1     2     2     0
##    probabilities: 0.643 0.071 0.143 0.143 0.000 
## 
## Node number 3086: 7 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.00035
##     class counts:     5     1     0     1     0
##    probabilities: 0.714 0.143 0.000 0.143 0.000 
## 
## Node number 3087: 21 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.7142857  P(node) =0.00105
##     class counts:     6     6     5     4     0
##    probabilities: 0.286 0.286 0.238 0.190 0.000 
##   left son=6174 (13 obs) right son=6175 (8 obs)
##   Primary splits:
##       reimbursement2008 < 2170   to the left,  improve=0.7921245, (0 missing)
##       age               < 84.5   to the right, improve=0.6190476, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3412698, (0 missing)
##   Surrogate splits:
##       age        < 82.5   to the right, agree=0.762, adj=0.375, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.667, adj=0.125, (0 split)
## 
## Node number 3112: 30 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0015
##     class counts:    20    10     0     0     0
##    probabilities: 0.667 0.333 0.000 0.000 0.000 
##   left son=6224 (23 obs) right son=6225 (7 obs)
##   Primary splits:
##       age               < 77.5   to the left,  improve=2.6501040, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.1111110, (0 missing)
##       reimbursement2008 < 2885   to the left,  improve=0.6625259, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.0297619, (0 missing)
## 
## Node number 3113: 11 observations
##   predicted class=B2  expected loss=0.3636364  P(node) =0.00055
##     class counts:     4     7     0     0     0
##    probabilities: 0.364 0.636 0.000 0.000 0.000 
## 
## Node number 3114: 18 observations
##   predicted class=B1  expected loss=0.2777778  P(node) =0.0009
##     class counts:    13     2     3     0     0
##    probabilities: 0.722 0.111 0.167 0.000 0.000 
## 
## Node number 3115: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     2     4     0     0     1
##    probabilities: 0.286 0.571 0.000 0.000 0.143 
## 
## Node number 3162: 17 observations
##   predicted class=B1  expected loss=0.4705882  P(node) =0.00085
##     class counts:     9     5     1     2     0
##    probabilities: 0.529 0.294 0.059 0.118 0.000 
## 
## Node number 3163: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     1     4     0     2     0
##    probabilities: 0.143 0.571 0.000 0.286 0.000 
## 
## Node number 3180: 8 observations
##   predicted class=B1  expected loss=0.125  P(node) =0.0004
##     class counts:     7     0     0     1     0
##    probabilities: 0.875 0.000 0.000 0.125 0.000 
## 
## Node number 3181: 105 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5809524  P(node) =0.00525
##     class counts:    44    37    21     2     1
##    probabilities: 0.419 0.352 0.200 0.019 0.010 
##   left son=6362 (45 obs) right son=6363 (60 obs)
##   Primary splits:
##       age               < 75.5   to the right, improve=1.0650790, (0 missing)
##       reimbursement2008 < 2955   to the left,  improve=0.9904762, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7462449, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.7161905, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6605234, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1930   to the left,  agree=0.610, adj=0.089, (0 split)
##       arthritis         < 0.5    to the right, agree=0.581, adj=0.022, (0 split)
## 
## Node number 3332: 70 observations
##   predicted class=B1  expected loss=0.3  P(node) =0.0035
##     class counts:    49    12     5     3     1
##    probabilities: 0.700 0.171 0.071 0.043 0.014 
## 
## Node number 3333: 16 observations
##   predicted class=B2  expected loss=0.5625  P(node) =0.0008
##     class counts:     6     7     2     1     0
##    probabilities: 0.375 0.438 0.125 0.062 0.000 
## 
## Node number 3334: 8 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.0004
##     class counts:     6     1     1     0     0
##    probabilities: 0.750 0.125 0.125 0.000 0.000 
## 
## Node number 3335: 50 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.54  P(node) =0.0025
##     class counts:    23    23     2     2     0
##    probabilities: 0.460 0.460 0.040 0.040 0.000 
##   left son=6670 (42 obs) right son=6671 (8 obs)
##   Primary splits:
##       age               < 89.5   to the left,  improve=0.7633333, (0 missing)
##       reimbursement2008 < 2305   to the left,  improve=0.5728571, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.4736508, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3203509, (0 missing)
##       kidney            < 0.5    to the right, improve=0.1300000, (0 missing)
## 
## Node number 3340: 33 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.4242424  P(node) =0.00165
##     class counts:    19    10     3     0     1
##    probabilities: 0.576 0.303 0.091 0.000 0.030 
##   left son=6680 (19 obs) right son=6681 (14 obs)
##   Primary splits:
##       age               < 77.5   to the right, improve=2.15584400, (0 missing)
##       reimbursement2008 < 1845   to the right, improve=0.38814230, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.37012990, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.22177820, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.03282828, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1690   to the right, agree=0.636, adj=0.143, (0 split)
## 
## Node number 3341: 30 observations,    complexity param=0.000190143
##   predicted class=B2  expected loss=0.4333333  P(node) =0.0015
##     class counts:    12    17     1     0     0
##    probabilities: 0.400 0.567 0.033 0.000 0.000 
##   left son=6682 (12 obs) right son=6683 (18 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=1.1444440, (0 missing)
##       reimbursement2008 < 2375   to the right, improve=0.9651515, (0 missing)
##       age               < 83     to the left,  improve=0.7188537, (0 missing)
##       kidney            < 0.5    to the right, improve=0.6015152, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.1469697, (0 missing)
## 
## Node number 3342: 10 observations
##   predicted class=B1  expected loss=0.2  P(node) =0.0005
##     class counts:     8     0     1     1     0
##    probabilities: 0.800 0.000 0.100 0.100 0.000 
## 
## Node number 3343: 15 observations
##   predicted class=B2  expected loss=0.6  P(node) =0.00075
##     class counts:     4     6     1     4     0
##    probabilities: 0.267 0.400 0.067 0.267 0.000 
## 
## Node number 3344: 211 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.3791469  P(node) =0.01055
##     class counts:   131    51    18    10     1
##    probabilities: 0.621 0.242 0.085 0.047 0.005 
##   left son=6688 (96 obs) right son=6689 (115 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=1.4607100, (0 missing)
##       reimbursement2008 < 1735   to the left,  improve=1.3331950, (0 missing)
##       age               < 70.5   to the left,  improve=1.0529550, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.7906734, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3086469, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2375   to the right, agree=0.564, adj=0.042, (0 split)
##       age               < 69.5   to the left,  agree=0.559, adj=0.031, (0 split)
##       cancer            < 0.5    to the right, agree=0.559, adj=0.031, (0 split)
## 
## Node number 3345: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     2     5     0     0     0
##    probabilities: 0.286 0.714 0.000 0.000 0.000 
## 
## Node number 3348: 18 observations
##   predicted class=B1  expected loss=0.5555556  P(node) =0.0009
##     class counts:     8     5     2     3     0
##    probabilities: 0.444 0.278 0.111 0.167 0.000 
## 
## Node number 3349: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     1     5     1     1     0
##    probabilities: 0.125 0.625 0.125 0.125 0.000 
## 
## Node number 3352: 98 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5714286  P(node) =0.0049
##     class counts:    41    42     6     8     1
##    probabilities: 0.418 0.429 0.061 0.082 0.010 
##   left son=6704 (88 obs) right son=6705 (10 obs)
##   Primary splits:
##       reimbursement2008 < 2165   to the left,  improve=1.2299630, (0 missing)
##       age               < 72.5   to the left,  improve=0.8171297, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.7814001, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5288983, (0 missing)
##       cancer            < 0.5    to the right, improve=0.4885488, (0 missing)
## 
## Node number 3353: 17 observations
##   predicted class=B1  expected loss=0.5882353  P(node) =0.00085
##     class counts:     7     4     5     0     1
##    probabilities: 0.412 0.235 0.294 0.000 0.059 
## 
## Node number 3354: 23 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.6086957  P(node) =0.00115
##     class counts:     8     9     6     0     0
##    probabilities: 0.348 0.391 0.261 0.000 0.000 
##   left son=6708 (16 obs) right son=6709 (7 obs)
##   Primary splits:
##       reimbursement2008 < 2305   to the right, improve=0.9697205, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.3880105, (0 missing)
##       age               < 70.5   to the right, improve=0.3150502, (0 missing)
## 
## Node number 3355: 8 observations
##   predicted class=B2  expected loss=0.25  P(node) =0.0004
##     class counts:     0     6     2     0     0
##    probabilities: 0.000 0.750 0.250 0.000 0.000 
## 
## Node number 3358: 8 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0004
##     class counts:     4     1     1     2     0
##    probabilities: 0.500 0.125 0.125 0.250 0.000 
## 
## Node number 3359: 17 observations
##   predicted class=B3  expected loss=0.5294118  P(node) =0.00085
##     class counts:     5     2     8     1     1
##    probabilities: 0.294 0.118 0.471 0.059 0.059 
## 
## Node number 3424: 28 observations
##   predicted class=B1  expected loss=0.2142857  P(node) =0.0014
##     class counts:    22     1     2     2     1
##    probabilities: 0.786 0.036 0.071 0.071 0.036 
## 
## Node number 3425: 34 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.4117647  P(node) =0.0017
##     class counts:    20    10     2     2     0
##    probabilities: 0.588 0.294 0.059 0.059 0.000 
##   left son=6850 (10 obs) right son=6851 (24 obs)
##   Primary splits:
##       reimbursement2008 < 1865   to the right, improve=1.9088240, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.1388240, (0 missing)
##       age               < 65.5   to the right, improve=1.0445380, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.4073084, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3640867, (0 missing)
##   Surrogate splits:
##       age < 37.5   to the left,  agree=0.765, adj=0.2, (0 split)
## 
## Node number 3428: 25 observations
##   predicted class=B1  expected loss=0.44  P(node) =0.00125
##     class counts:    14     7     3     1     0
##    probabilities: 0.560 0.280 0.120 0.040 0.000 
## 
## Node number 3429: 29 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6551724  P(node) =0.00145
##     class counts:     7    10     9     3     0
##    probabilities: 0.241 0.345 0.310 0.103 0.000 
##   left son=6858 (22 obs) right son=6859 (7 obs)
##   Primary splits:
##       age               < 55     to the right, improve=1.5638150, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.2323050, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.9144648, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.6007260, (0 missing)
##       reimbursement2008 < 2075   to the right, improve=0.5667015, (0 missing)
##   Surrogate splits:
##       kidney < 0.5    to the left,  agree=0.793, adj=0.143, (0 split)
## 
## Node number 3434: 10 observations
##   predicted class=B2  expected loss=0.2  P(node) =0.0005
##     class counts:     2     8     0     0     0
##    probabilities: 0.200 0.800 0.000 0.000 0.000 
## 
## Node number 3435: 99 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.4949495  P(node) =0.00495
##     class counts:    32    50    16     1     0
##    probabilities: 0.323 0.505 0.162 0.010 0.000 
##   left son=6870 (46 obs) right son=6871 (53 obs)
##   Primary splits:
##       reimbursement2008 < 2045   to the right, improve=1.4422070, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.6616256, (0 missing)
##       age               < 75.5   to the right, improve=0.5566090, (0 missing)
##       copd              < 0.5    to the right, improve=0.5057552, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.4451178, (0 missing)
##   Surrogate splits:
##       age          < 72.5   to the left,  agree=0.576, adj=0.087, (0 split)
##       diabetes     < 0.5    to the right, agree=0.566, adj=0.065, (0 split)
##       arthritis    < 0.5    to the right, agree=0.556, adj=0.043, (0 split)
##       kidney       < 0.5    to the right, agree=0.556, adj=0.043, (0 split)
##       osteoporosis < 0.5    to the right, agree=0.556, adj=0.043, (0 split)
## 
## Node number 3466: 14 observations
##   predicted class=B1  expected loss=0.2142857  P(node) =0.0007
##     class counts:    11     2     0     1     0
##    probabilities: 0.786 0.143 0.000 0.071 0.000 
## 
## Node number 3467: 55 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5090909  P(node) =0.00275
##     class counts:    27    17     8     3     0
##    probabilities: 0.491 0.309 0.145 0.055 0.000 
##   left son=6934 (41 obs) right son=6935 (14 obs)
##   Primary splits:
##       age               < 83.5   to the left,  improve=2.7071900, (0 missing)
##       reimbursement2008 < 2680   to the right, improve=1.7662000, (0 missing)
##       copd              < 0.5    to the left,  improve=1.5148270, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.3909091, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1531834, (0 missing)
## 
## Node number 3468: 58 observations,    complexity param=0.0001014096
##   predicted class=B1  expected loss=0.4310345  P(node) =0.0029
##     class counts:    33    11    10     2     2
##    probabilities: 0.569 0.190 0.172 0.034 0.034 
##   left son=6936 (7 obs) right son=6937 (51 obs)
##   Primary splits:
##       reimbursement2008 < 3325   to the right, improve=2.0209600, (0 missing)
##       age               < 70.5   to the right, improve=0.7361795, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.5862069, (0 missing)
##       kidney            < 0.5    to the right, improve=0.3220159, (0 missing)
##       copd              < 0.5    to the left,  improve=0.2258621, (0 missing)
## 
## Node number 3469: 46 observations,    complexity param=0.0002662002
##   predicted class=B2  expected loss=0.6086957  P(node) =0.0023
##     class counts:    17    18     9     2     0
##    probabilities: 0.370 0.391 0.196 0.043 0.000 
##   left son=6938 (33 obs) right son=6939 (13 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=1.2037090, (0 missing)
##       age               < 81.5   to the right, improve=0.9942551, (0 missing)
##       reimbursement2008 < 2695   to the left,  improve=0.9260870, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7830762, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4167302, (0 missing)
##   Surrogate splits:
##       copd              < 0.5    to the left,  agree=0.783, adj=0.231, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.739, adj=0.077, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.739, adj=0.077, (0 split)
##       reimbursement2008 < 3385   to the left,  agree=0.739, adj=0.077, (0 split)
## 
## Node number 3490: 67 observations,    complexity param=0.000253524
##   predicted class=B1  expected loss=0.4626866  P(node) =0.00335
##     class counts:    36    18     6     7     0
##    probabilities: 0.537 0.269 0.090 0.104 0.000 
##   left son=6980 (23 obs) right son=6981 (44 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=1.7004600, (0 missing)
##       reimbursement2008 < 2850   to the right, improve=0.8931479, (0 missing)
##       age               < 87.5   to the right, improve=0.8361371, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5107368, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4996072, (0 missing)
##   Surrogate splits:
##       age    < 41.5   to the left,  agree=0.687, adj=0.087, (0 split)
##       stroke < 0.5    to the right, agree=0.672, adj=0.043, (0 split)
## 
## Node number 3491: 58 observations,    complexity param=0.0006084576
##   predicted class=B2  expected loss=0.5  P(node) =0.0029
##     class counts:    20    29     5     4     0
##    probabilities: 0.345 0.500 0.086 0.069 0.000 
##   left son=6982 (13 obs) right son=6983 (45 obs)
##   Primary splits:
##       age               < 67.5   to the left,  improve=1.9273210, (0 missing)
##       reimbursement2008 < 3285   to the right, improve=1.2543850, (0 missing)
##       depression        < 0.5    to the left,  improve=1.0681200, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6646677, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.3607892, (0 missing)
## 
## Node number 3502: 39 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.6923077  P(node) =0.00195
##     class counts:    12    12     9     6     0
##    probabilities: 0.308 0.308 0.231 0.154 0.000 
##   left son=7004 (19 obs) right son=7005 (20 obs)
##   Primary splits:
##       reimbursement2008 < 3120   to the right, improve=1.4732790, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=1.0783480, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7169889, (0 missing)
##       age               < 79.5   to the left,  improve=0.6923077, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6923077, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the right, agree=0.795, adj=0.579, (0 split)
##       depression < 0.5    to the right, agree=0.641, adj=0.263, (0 split)
##       age        < 79.5   to the left,  agree=0.615, adj=0.211, (0 split)
##       diabetes   < 0.5    to the left,  agree=0.615, adj=0.211, (0 split)
##       copd       < 0.5    to the right, agree=0.590, adj=0.158, (0 split)
## 
## Node number 3503: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     0     2     4     1     0
##    probabilities: 0.000 0.286 0.571 0.143 0.000 
## 
## Node number 3520: 40 observations,    complexity param=0.0002788764
##   predicted class=B1  expected loss=0.55  P(node) =0.002
##     class counts:    18    15     5     1     1
##    probabilities: 0.450 0.375 0.125 0.025 0.025 
##   left son=7040 (32 obs) right son=7041 (8 obs)
##   Primary splits:
##       age          < 80.5   to the left,  improve=1.4125000, (0 missing)
##       osteoporosis < 0.5    to the left,  improve=1.0583330, (0 missing)
##       copd         < 0.5    to the left,  improve=0.8022792, (0 missing)
##       depression   < 0.5    to the left,  improve=0.7111111, (0 missing)
##       diabetes     < 0.5    to the left,  improve=0.2933333, (0 missing)
## 
## Node number 3521: 64 observations,    complexity param=0.0002788764
##   predicted class=B2  expected loss=0.5  P(node) =0.0032
##     class counts:    20    32     9     3     0
##    probabilities: 0.312 0.500 0.141 0.047 0.000 
##   left son=7042 (52 obs) right son=7043 (12 obs)
##   Primary splits:
##       reimbursement2008 < 2565   to the right, improve=1.3052880, (0 missing)
##       age               < 72     to the right, improve=1.1374010, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6240303, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.4687500, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.4238501, (0 missing)
## 
## Node number 3522: 12 observations
##   predicted class=B2  expected loss=0.4166667  P(node) =0.0006
##     class counts:     4     7     1     0     0
##    probabilities: 0.333 0.583 0.083 0.000 0.000 
## 
## Node number 3523: 26 observations,    complexity param=0.0001521144
##   predicted class=B3  expected loss=0.5384615  P(node) =0.0013
##     class counts:     7     7    12     0     0
##    probabilities: 0.269 0.269 0.462 0.000 0.000 
##   left son=7046 (19 obs) right son=7047 (7 obs)
##   Primary splits:
##       diabetes          < 0.5    to the right, improve=2.3464430, (0 missing)
##       copd              < 0.5    to the left,  improve=1.3088490, (0 missing)
##       reimbursement2008 < 2640   to the right, improve=1.3088490, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.9423077, (0 missing)
##       age               < 68     to the left,  improve=0.7707391, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2620   to the right, agree=0.885, adj=0.571, (0 split)
##       copd              < 0.5    to the left,  agree=0.769, adj=0.143, (0 split)
## 
## Node number 3554: 11 observations
##   predicted class=B1  expected loss=0.1818182  P(node) =0.00055
##     class counts:     9     2     0     0     0
##    probabilities: 0.818 0.182 0.000 0.000 0.000 
## 
## Node number 3555: 18 observations
##   predicted class=B2  expected loss=0.6111111  P(node) =0.0009
##     class counts:     5     7     4     1     1
##    probabilities: 0.278 0.389 0.222 0.056 0.056 
## 
## Node number 3590: 23 observations
##   predicted class=B1  expected loss=0.3913043  P(node) =0.00115
##     class counts:    14     6     2     1     0
##    probabilities: 0.609 0.261 0.087 0.043 0.000 
## 
## Node number 3591: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     2     4     1     0     0
##    probabilities: 0.286 0.571 0.143 0.000 0.000 
## 
## Node number 3594: 56 observations
##   predicted class=B1  expected loss=0.375  P(node) =0.0028
##     class counts:    35    15     3     2     1
##    probabilities: 0.625 0.268 0.054 0.036 0.018 
## 
## Node number 3595: 11 observations
##   predicted class=B2  expected loss=0.6363636  P(node) =0.00055
##     class counts:     3     4     3     1     0
##    probabilities: 0.273 0.364 0.273 0.091 0.000 
## 
## Node number 3596: 8 observations
##   predicted class=B1  expected loss=0.125  P(node) =0.0004
##     class counts:     7     1     0     0     0
##    probabilities: 0.875 0.125 0.000 0.000 0.000 
## 
## Node number 3597: 97 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.4639175  P(node) =0.00485
##     class counts:    52    26    17     2     0
##    probabilities: 0.536 0.268 0.175 0.021 0.000 
##   left son=7194 (79 obs) right son=7195 (18 obs)
##   Primary splits:
##       age               < 81.5   to the left,  improve=2.2155960, (0 missing)
##       reimbursement2008 < 5125   to the right, improve=1.6287330, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8331981, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.7669320, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.2559504, (0 missing)
## 
## Node number 3610: 22 observations
##   predicted class=B2  expected loss=0.4090909  P(node) =0.0011
##     class counts:     7    13     1     1     0
##    probabilities: 0.318 0.591 0.045 0.045 0.000 
## 
## Node number 3611: 12 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0006
##     class counts:     6     3     2     1     0
##    probabilities: 0.500 0.250 0.167 0.083 0.000 
## 
## Node number 3644: 7 observations
##   predicted class=B2  expected loss=0.1428571  P(node) =0.00035
##     class counts:     1     6     0     0     0
##    probabilities: 0.143 0.857 0.000 0.000 0.000 
## 
## Node number 3645: 15 observations
##   predicted class=B1  expected loss=0.6  P(node) =0.00075
##     class counts:     6     5     3     1     0
##    probabilities: 0.400 0.333 0.200 0.067 0.000 
## 
## Node number 3646: 9 observations
##   predicted class=B1  expected loss=0.5555556  P(node) =0.00045
##     class counts:     4     3     1     1     0
##    probabilities: 0.444 0.333 0.111 0.111 0.000 
## 
## Node number 3647: 23 observations
##   predicted class=B3  expected loss=0.4782609  P(node) =0.00115
##     class counts:     7     4    12     0     0
##    probabilities: 0.304 0.174 0.522 0.000 0.000 
## 
## Node number 3750: 13 observations
##   predicted class=B2  expected loss=0.1538462  P(node) =0.00065
##     class counts:     2    11     0     0     0
##    probabilities: 0.154 0.846 0.000 0.000 0.000 
## 
## Node number 3751: 25 observations,    complexity param=7.60572e-05
##   predicted class=B2  expected loss=0.48  P(node) =0.00125
##     class counts:     6    13     4     2     0
##    probabilities: 0.240 0.520 0.160 0.080 0.000 
##   left son=7502 (10 obs) right son=7503 (15 obs)
##   Primary splits:
##       reimbursement2008 < 5090   to the left,  improve=1.2666670, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.4558824, (0 missing)
##       age               < 71.5   to the left,  improve=0.3461538, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3174603, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.2500000, (0 missing)
##   Surrogate splits:
##       age       < 71.5   to the right, agree=0.72, adj=0.3, (0 split)
##       cancer    < 0.5    to the left,  agree=0.72, adj=0.3, (0 split)
##       arthritis < 0.5    to the right, agree=0.64, adj=0.1, (0 split)
## 
## Node number 3758: 25 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.52  P(node) =0.00125
##     class counts:     5    12     6     2     0
##    probabilities: 0.200 0.480 0.240 0.080 0.000 
##   left son=7516 (18 obs) right son=7517 (7 obs)
##   Primary splits:
##       reimbursement2008 < 19195  to the left,  improve=0.7828571, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=0.7828571, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.5733333, (0 missing)
##       age               < 71.5   to the right, improve=0.5370588, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.0374359, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the left,  agree=1.00, adj=1.000, (0 split)
##       cancer     < 0.5    to the left,  agree=0.80, adj=0.286, (0 split)
##       age        < 69.5   to the right, agree=0.76, adj=0.143, (0 split)
##       stroke     < 0.5    to the left,  agree=0.76, adj=0.143, (0 split)
## 
## Node number 3759: 14 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.0007
##     class counts:     4     1     8     1     0
##    probabilities: 0.286 0.071 0.571 0.071 0.000 
## 
## Node number 3824: 15 observations
##   predicted class=B1  expected loss=0.4666667  P(node) =0.00075
##     class counts:     8     4     3     0     0
##    probabilities: 0.533 0.267 0.200 0.000 0.000 
## 
## Node number 3825: 15 observations
##   predicted class=B2  expected loss=0.5333333  P(node) =0.00075
##     class counts:     3     7     2     3     0
##    probabilities: 0.200 0.467 0.133 0.200 0.000 
## 
## Node number 3840: 8 observations
##   predicted class=B1  expected loss=0.375  P(node) =0.0004
##     class counts:     5     2     1     0     0
##    probabilities: 0.625 0.250 0.125 0.000 0.000 
## 
## Node number 3841: 24 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4583333  P(node) =0.0012
##     class counts:    10    13     1     0     0
##    probabilities: 0.417 0.542 0.042 0.000 0.000 
##   left son=7682 (7 obs) right son=7683 (17 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=0.38025210, (0 missing)
##       reimbursement2008 < 6890   to the right, improve=0.35000000, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.17222220, (0 missing)
##       age               < 67.5   to the right, improve=0.12500000, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.02731092, (0 missing)
##   Surrogate splits:
##       age           < 66.5   to the left,  agree=0.75, adj=0.143, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.75, adj=0.143, (0 split)
## 
## Node number 3842: 19 observations
##   predicted class=B1  expected loss=0.2105263  P(node) =0.00095
##     class counts:    15     1     3     0     0
##    probabilities: 0.789 0.053 0.158 0.000 0.000 
## 
## Node number 3843: 104 observations,    complexity param=0.0003422574
##   predicted class=B1  expected loss=0.5480769  P(node) =0.0052
##     class counts:    47    31    23     3     0
##    probabilities: 0.452 0.298 0.221 0.029 0.000 
##   left son=7686 (76 obs) right son=7687 (28 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=2.6920190, (0 missing)
##       reimbursement2008 < 3815   to the left,  improve=2.1500750, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9947414, (0 missing)
##       age               < 45.5   to the left,  improve=0.6525368, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5917679, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4710   to the left,  agree=0.769, adj=0.143, (0 split)
##       stroke            < 0.5    to the left,  agree=0.740, adj=0.036, (0 split)
## 
## Node number 3848: 7 observations
##   predicted class=B1  expected loss=0.1428571  P(node) =0.00035
##     class counts:     6     1     0     0     0
##    probabilities: 0.857 0.143 0.000 0.000 0.000 
## 
## Node number 3849: 24 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5833333  P(node) =0.0012
##     class counts:     6    10     2     5     1
##    probabilities: 0.250 0.417 0.083 0.208 0.042 
##   left son=7698 (9 obs) right son=7699 (15 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=1.2611110, (0 missing)
##       age               < 58.5   to the left,  improve=1.2083330, (0 missing)
##       reimbursement2008 < 24480  to the left,  improve=0.9488796, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7083333, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3119048, (0 missing)
##   Surrogate splits:
##       age               < 50.5   to the left,  agree=0.708, adj=0.222, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.667, adj=0.111, (0 split)
##       reimbursement2008 < 19645  to the right, agree=0.667, adj=0.111, (0 split)
##       bucket2008        < 3.5    to the right, agree=0.667, adj=0.111, (0 split)
## 
## Node number 3850: 13 observations
##   predicted class=B3  expected loss=0.5384615  P(node) =0.00065
##     class counts:     2     3     6     2     0
##    probabilities: 0.154 0.231 0.462 0.154 0.000 
## 
## Node number 3851: 8 observations
##   predicted class=B4  expected loss=0.625  P(node) =0.0004
##     class counts:     2     2     1     3     0
##    probabilities: 0.250 0.250 0.125 0.375 0.000 
## 
## Node number 3856: 117 observations,    complexity param=0.0003295812
##   predicted class=B1  expected loss=0.4786325  P(node) =0.00585
##     class counts:    61    35    13     8     0
##    probabilities: 0.521 0.299 0.111 0.068 0.000 
##   left son=7712 (11 obs) right son=7713 (106 obs)
##   Primary splits:
##       reimbursement2008 < 5335   to the left,  improve=1.6681470, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.5859199, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5517094, (0 missing)
##       age               < 82.5   to the left,  improve=0.5042735, (0 missing)
##       copd              < 0.5    to the right, improve=0.4257959, (0 missing)
## 
## Node number 3857: 27 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.4814815  P(node) =0.00135
##     class counts:    10    14     2     1     0
##    probabilities: 0.370 0.519 0.074 0.037 0.000 
##   left son=7714 (13 obs) right son=7715 (14 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the right, improve=1.1925110, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.0740740, (0 missing)
##       reimbursement2008 < 8000   to the left,  improve=0.6980057, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.6980057, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3386940, (0 missing)
##   Surrogate splits:
##       alzheimers        < 0.5    to the left,  agree=0.667, adj=0.308, (0 split)
##       ihd               < 0.5    to the right, agree=0.593, adj=0.154, (0 split)
##       reimbursement2008 < 7825   to the right, agree=0.593, adj=0.154, (0 split)
##       bucket2008        < 3.5    to the right, agree=0.593, adj=0.154, (0 split)
##       age               < 71.5   to the right, agree=0.556, adj=0.077, (0 split)
## 
## Node number 3858: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     1     5     1     0     0
##    probabilities: 0.143 0.714 0.143 0.000 0.000 
## 
## Node number 3859: 19 observations
##   predicted class=B3  expected loss=0.6315789  P(node) =0.00095
##     class counts:     6     4     7     1     1
##    probabilities: 0.316 0.211 0.368 0.053 0.053 
## 
## Node number 3860: 17 observations
##   predicted class=B1  expected loss=0.2941176  P(node) =0.00085
##     class counts:    12     2     1     2     0
##    probabilities: 0.706 0.118 0.059 0.118 0.000 
## 
## Node number 3861: 11 observations
##   predicted class=B2  expected loss=0.3636364  P(node) =0.00055
##     class counts:     3     7     0     0     1
##    probabilities: 0.273 0.636 0.000 0.000 0.091 
## 
## Node number 3862: 61 observations,    complexity param=0.0004056384
##   predicted class=B2  expected loss=0.4262295  P(node) =0.00305
##     class counts:    14    35    10     2     0
##    probabilities: 0.230 0.574 0.164 0.033 0.000 
##   left son=7724 (14 obs) right son=7725 (47 obs)
##   Primary splits:
##       reimbursement2008 < 14285  to the right, improve=2.9027360, (0 missing)
##       age               < 81.5   to the left,  improve=2.7429190, (0 missing)
##       stroke            < 0.5    to the right, improve=0.7350427, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6774892, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.6382429, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.869, adj=0.429, (0 split)
## 
## Node number 3863: 68 observations,    complexity param=0.0004056384
##   predicted class=B2  expected loss=0.6617647  P(node) =0.0034
##     class counts:    20    23    16     8     1
##    probabilities: 0.294 0.338 0.235 0.118 0.015 
##   left son=7726 (49 obs) right son=7727 (19 obs)
##   Primary splits:
##       reimbursement2008 < 7090   to the right, improve=2.0709230, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.9533610, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.8022620, (0 missing)
##       copd              < 0.5    to the left,  improve=1.4319330, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.9282531, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.926, adj=0.737, (0 split)
##       age        < 87.5   to the left,  agree=0.735, adj=0.053, (0 split)
## 
## Node number 3864: 50 observations
##   predicted class=B2  expected loss=0.3  P(node) =0.0025
##     class counts:    11    35     2     2     0
##    probabilities: 0.220 0.700 0.040 0.040 0.000 
## 
## Node number 3865: 14 observations
##   predicted class=B1  expected loss=0.5714286  P(node) =0.0007
##     class counts:     6     3     5     0     0
##    probabilities: 0.429 0.214 0.357 0.000 0.000 
## 
## Node number 3870: 37 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.6216216  P(node) =0.00185
##     class counts:    14    14     6     3     0
##    probabilities: 0.378 0.378 0.162 0.081 0.000 
##   left son=7740 (17 obs) right son=7741 (20 obs)
##   Primary splits:
##       reimbursement2008 < 4035   to the left,  improve=1.0186010, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6996787, (0 missing)
##       age               < 87.5   to the right, improve=0.6571379, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6256971, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.5308041, (0 missing)
##   Surrogate splits:
##       age           < 90.5   to the right, agree=0.595, adj=0.118, (0 split)
##       copd          < 0.5    to the left,  agree=0.595, adj=0.118, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.568, adj=0.059, (0 split)
## 
## Node number 3871: 67 observations
##   predicted class=B2  expected loss=0.4179104  P(node) =0.00335
##     class counts:    14    39    12     2     0
##    probabilities: 0.209 0.582 0.179 0.030 0.000 
## 
## Node number 3892: 16 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0008
##     class counts:     8     4     2     2     0
##    probabilities: 0.500 0.250 0.125 0.125 0.000 
## 
## Node number 3893: 33 observations,    complexity param=0.0004563432
##   predicted class=B3  expected loss=0.5757576  P(node) =0.00165
##     class counts:     8     9    14     2     0
##    probabilities: 0.242 0.273 0.424 0.061 0.000 
##   left son=7786 (11 obs) right son=7787 (22 obs)
##   Primary splits:
##       reimbursement2008 < 5825   to the left,  improve=2.0909090, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.5680110, (0 missing)
##       age               < 66.5   to the right, improve=1.4575420, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.3232320, (0 missing)
##       depression        < 0.5    to the left,  improve=0.8073593, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.788, adj=0.364, (0 split)
##       ihd        < 0.5    to the left,  agree=0.758, adj=0.273, (0 split)
## 
## Node number 3894: 33 observations,    complexity param=7.60572e-05
##   predicted class=B3  expected loss=0.5757576  P(node) =0.00165
##     class counts:     7     9    14     3     0
##    probabilities: 0.212 0.273 0.424 0.091 0.000 
##   left son=7788 (26 obs) right son=7789 (7 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=1.4748580, (0 missing)
##       copd              < 0.5    to the left,  improve=1.3210120, (0 missing)
##       reimbursement2008 < 14730  to the left,  improve=0.7056277, (0 missing)
##       age               < 76.5   to the right, improve=0.6905901, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5151515, (0 missing)
## 
## Node number 3895: 30 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4333333  P(node) =0.0015
##     class counts:     1    17     8     4     0
##    probabilities: 0.033 0.567 0.267 0.133 0.000 
##   left son=7790 (13 obs) right son=7791 (17 obs)
##   Primary splits:
##       age               < 75.5   to the left,  improve=2.7164400, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.2202380, (0 missing)
##       reimbursement2008 < 6230   to the left,  improve=1.0828160, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.6236045, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4896332, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4310   to the left,  agree=0.700, adj=0.308, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.667, adj=0.231, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.600, adj=0.077, (0 split)
##       stroke            < 0.5    to the right, agree=0.600, adj=0.077, (0 split)
## 
## Node number 3936: 30 observations
##   predicted class=B1  expected loss=0.4333333  P(node) =0.0015
##     class counts:    17    10     1     1     1
##    probabilities: 0.567 0.333 0.033 0.033 0.033 
## 
## Node number 3937: 8 observations
##   predicted class=B4  expected loss=0.625  P(node) =0.0004
##     class counts:     2     2     1     3     0
##    probabilities: 0.250 0.250 0.125 0.375 0.000 
## 
## Node number 3940: 59 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.4915254  P(node) =0.00295
##     class counts:    19    30     6     3     1
##    probabilities: 0.322 0.508 0.102 0.051 0.017 
##   left son=7880 (7 obs) right son=7881 (52 obs)
##   Primary splits:
##       reimbursement2008 < 4180   to the left,  improve=2.3199850, (0 missing)
##       age               < 74.5   to the right, improve=1.6846670, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7680925, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4469662, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.3751074, (0 missing)
## 
## Node number 3941: 26 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.6923077  P(node) =0.0013
##     class counts:     8     8     5     5     0
##    probabilities: 0.308 0.308 0.192 0.192 0.000 
##   left son=7882 (18 obs) right son=7883 (8 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=1.5705130, (0 missing)
##       age               < 90.5   to the right, improve=1.5147480, (0 missing)
##       reimbursement2008 < 5065   to the left,  improve=1.3038460, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5586081, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5072296, (0 missing)
##   Surrogate splits:
##       copd < 0.5    to the left,  agree=0.731, adj=0.125, (0 split)
## 
## Node number 3942: 32 observations
##   predicted class=B2  expected loss=0.34375  P(node) =0.0016
##     class counts:     1    21     4     6     0
##    probabilities: 0.031 0.656 0.125 0.187 0.000 
## 
## Node number 3943: 10 observations
##   predicted class=B1  expected loss=0.7  P(node) =0.0005
##     class counts:     3     2     2     3     0
##    probabilities: 0.300 0.200 0.200 0.300 0.000 
## 
## Node number 3946: 10 observations
##   predicted class=B2  expected loss=0.4  P(node) =0.0005
##     class counts:     2     6     0     2     0
##    probabilities: 0.200 0.600 0.000 0.200 0.000 
## 
## Node number 3947: 11 observations
##   predicted class=B4  expected loss=0.5454545  P(node) =0.00055
##     class counts:     2     3     1     5     0
##    probabilities: 0.182 0.273 0.091 0.455 0.000 
## 
## Node number 3950: 23 observations
##   predicted class=B2  expected loss=0.3043478  P(node) =0.00115
##     class counts:     2    16     3     2     0
##    probabilities: 0.087 0.696 0.130 0.087 0.000 
## 
## Node number 3951: 22 observations,    complexity param=0.0001521144
##   predicted class=B3  expected loss=0.5  P(node) =0.0011
##     class counts:     3     8    11     0     0
##    probabilities: 0.136 0.364 0.500 0.000 0.000 
##   left son=7902 (15 obs) right son=7903 (7 obs)
##   Primary splits:
##       reimbursement2008 < 6650   to the right, improve=2.0008660, (0 missing)
##       copd              < 0.5    to the right, improve=1.9246750, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.7630150, (0 missing)
##       age               < 72.5   to the left,  improve=0.9722944, (0 missing)
##   Surrogate splits:
##       age           < 64.5   to the right, agree=0.727, adj=0.143, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.727, adj=0.143, (0 split)
##       ihd           < 0.5    to the right, agree=0.727, adj=0.143, (0 split)
##       stroke        < 0.5    to the left,  agree=0.727, adj=0.143, (0 split)
## 
## Node number 3956: 52 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.4230769  P(node) =0.0026
##     class counts:     8    30    10     4     0
##    probabilities: 0.154 0.577 0.192 0.077 0.000 
##   left son=7912 (30 obs) right son=7913 (22 obs)
##   Primary splits:
##       reimbursement2008 < 23850  to the left,  improve=3.0974360, (0 missing)
##       age               < 77.5   to the right, improve=1.7192480, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=1.1057690, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8778281, (0 missing)
##       cancer            < 0.5    to the right, improve=0.6335470, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the left,  agree=0.731, adj=0.364, (0 split)
##       cancer     < 0.5    to the left,  agree=0.615, adj=0.091, (0 split)
##       age        < 59     to the right, agree=0.596, adj=0.045, (0 split)
##       stroke     < 0.5    to the left,  agree=0.596, adj=0.045, (0 split)
## 
## Node number 3957: 164 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5853659  P(node) =0.0082
##     class counts:    34    68    46    14     2
##    probabilities: 0.207 0.415 0.280 0.085 0.012 
##   left son=7914 (90 obs) right son=7915 (74 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=1.4857980, (0 missing)
##       reimbursement2008 < 4235   to the right, improve=1.2625250, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.1619200, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.0523830, (0 missing)
##       age               < 89.5   to the right, improve=0.8063318, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 9795   to the left,  agree=0.604, adj=0.122, (0 split)
##       copd              < 0.5    to the left,  agree=0.598, adj=0.108, (0 split)
##       age               < 85.5   to the left,  agree=0.585, adj=0.081, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.585, adj=0.081, (0 split)
##       ihd               < 0.5    to the right, agree=0.579, adj=0.068, (0 split)
## 
## Node number 3968: 11 observations
##   predicted class=B1  expected loss=0.2727273  P(node) =0.00055
##     class counts:     8     0     3     0     0
##    probabilities: 0.727 0.000 0.273 0.000 0.000 
## 
## Node number 3969: 32 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.6875  P(node) =0.0016
##     class counts:    10     9     9     2     2
##    probabilities: 0.312 0.281 0.281 0.062 0.062 
##   left son=7938 (24 obs) right son=7939 (8 obs)
##   Primary splits:
##       age               < 96.5   to the left,  improve=1.8958330, (0 missing)
##       copd              < 0.5    to the right, improve=1.4291670, (0 missing)
##       reimbursement2008 < 10790  to the right, improve=0.8539286, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6875000, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3878968, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 10790  to the right, agree=0.781, adj=0.125, (0 split)
## 
## Node number 3970: 8 observations
##   predicted class=B2  expected loss=0.25  P(node) =0.0004
##     class counts:     0     6     2     0     0
##    probabilities: 0.000 0.750 0.250 0.000 0.000 
## 
## Node number 3971: 16 observations
##   predicted class=B3  expected loss=0.5625  P(node) =0.0008
##     class counts:     4     3     7     2     0
##    probabilities: 0.250 0.188 0.438 0.125 0.000 
## 
## Node number 3974: 177 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6101695  P(node) =0.00885
##     class counts:    46    69    25    32     5
##    probabilities: 0.260 0.390 0.141 0.181 0.028 
##   left son=7948 (169 obs) right son=7949 (8 obs)
##   Primary splits:
##       reimbursement2008 < 14365  to the left,  improve=2.4954790, (0 missing)
##       age               < 75.5   to the right, improve=1.9376320, (0 missing)
##       stroke            < 0.5    to the right, improve=0.7544507, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.6832293, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.5905001, (0 missing)
## 
## Node number 3975: 91 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6483516  P(node) =0.00455
##     class counts:    14    32    24    18     3
##    probabilities: 0.154 0.352 0.264 0.198 0.033 
##   left son=7950 (34 obs) right son=7951 (57 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=1.981073, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.924030, (0 missing)
##       depression        < 0.5    to the left,  improve=1.545458, (0 missing)
##       reimbursement2008 < 9695   to the right, improve=1.218681, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.168681, (0 missing)
##   Surrogate splits:
##       ihd < 0.5    to the left,  agree=0.67, adj=0.118, (0 split)
## 
## Node number 3980: 210 observations,    complexity param=0.0003650745
##   predicted class=B2  expected loss=0.6047619  P(node) =0.0105
##     class counts:    44    83    47    31     5
##    probabilities: 0.210 0.395 0.224 0.148 0.024 
##   left son=7960 (48 obs) right son=7961 (162 obs)
##   Primary splits:
##       age               < 81.5   to the right, improve=1.422399, (0 missing)
##       ihd               < 0.5    to the right, improve=1.305861, (0 missing)
##       reimbursement2008 < 4080   to the left,  improve=1.052847, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.007552, (0 missing)
##       depression        < 0.5    to the right, improve=0.922645, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 6050   to the right, agree=0.776, adj=0.021, (0 split)
## 
## Node number 3981: 25 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.52  P(node) =0.00125
##     class counts:     1    10    12     1     1
##    probabilities: 0.040 0.400 0.480 0.040 0.040 
##   left son=7962 (17 obs) right son=7963 (8 obs)
##   Primary splits:
##       reimbursement2008 < 6260   to the right, improve=1.3258820, (0 missing)
##       age               < 67.5   to the right, improve=0.7073016, (0 missing)
##       depression        < 0.5    to the right, improve=0.4661538, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4576623, (0 missing)
##       copd              < 0.5    to the right, improve=0.2588889, (0 missing)
##   Surrogate splits:
##       age < 75     to the left,  agree=0.72, adj=0.125, (0 split)
## 
## Node number 4008: 19 observations
##   predicted class=B2  expected loss=0.2631579  P(node) =0.00095
##     class counts:     2    14     1     2     0
##    probabilities: 0.105 0.737 0.053 0.105 0.000 
## 
## Node number 4009: 69 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.4782609  P(node) =0.00345
##     class counts:    14    36    13     5     1
##    probabilities: 0.203 0.522 0.188 0.072 0.014 
##   left son=8018 (29 obs) right son=8019 (40 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=1.4558970, (0 missing)
##       age               < 81.5   to the right, improve=1.2755920, (0 missing)
##       reimbursement2008 < 3895   to the left,  improve=1.2388600, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6811594, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6025765, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 3955   to the left,  agree=0.667, adj=0.207, (0 split)
##       age               < 93     to the right, agree=0.623, adj=0.103, (0 split)
##       depression        < 0.5    to the right, agree=0.623, adj=0.103, (0 split)
## 
## Node number 4024: 13 observations
##   predicted class=B2  expected loss=0.5384615  P(node) =0.00065
##     class counts:     3     6     2     2     0
##    probabilities: 0.231 0.462 0.154 0.154 0.000 
## 
## Node number 4025: 22 observations
##   predicted class=B3  expected loss=0.5454545  P(node) =0.0011
##     class counts:     4     5    10     3     0
##    probabilities: 0.182 0.227 0.455 0.136 0.000 
## 
## Node number 4026: 187 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5347594  P(node) =0.00935
##     class counts:    20    87    53    22     5
##    probabilities: 0.107 0.465 0.283 0.118 0.027 
##   left son=8052 (35 obs) right son=8053 (152 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=0.9804330, (0 missing)
##       reimbursement2008 < 7580   to the right, improve=0.9500758, (0 missing)
##       age               < 75.5   to the left,  improve=0.9208236, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8858296, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.6009844, (0 missing)
## 
## Node number 4027: 31 observations
##   predicted class=B2  expected loss=0.4516129  P(node) =0.00155
##     class counts:     2    17     4     8     0
##    probabilities: 0.065 0.548 0.129 0.258 0.000 
## 
## Node number 4064: 59 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.6610169  P(node) =0.00295
##     class counts:    20    12    12    15     0
##    probabilities: 0.339 0.203 0.203 0.254 0.000 
##   left son=8128 (10 obs) right son=8129 (49 obs)
##   Primary splits:
##       stroke            < 0.5    to the right, improve=2.0111380, (0 missing)
##       cancer            < 0.5    to the right, improve=1.1459910, (0 missing)
##       reimbursement2008 < 19645  to the right, improve=1.0270110, (0 missing)
##       age               < 80     to the left,  improve=0.9767058, (0 missing)
##       depression        < 0.5    to the right, improve=0.7631860, (0 missing)
## 
## Node number 4065: 8 observations
##   predicted class=B3  expected loss=0.375  P(node) =0.0004
##     class counts:     2     0     5     1     0
##    probabilities: 0.250 0.000 0.625 0.125 0.000 
## 
## Node number 4066: 9 observations
##   predicted class=B1  expected loss=0.6666667  P(node) =0.00045
##     class counts:     3     1     3     2     0
##    probabilities: 0.333 0.111 0.333 0.222 0.000 
## 
## Node number 4067: 19 observations
##   predicted class=B2  expected loss=0.4736842  P(node) =0.00095
##     class counts:     2    10     0     7     0
##    probabilities: 0.105 0.526 0.000 0.368 0.000 
## 
## Node number 4068: 32 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.40625  P(node) =0.0016
##     class counts:     4    19     4     3     2
##    probabilities: 0.125 0.594 0.125 0.094 0.062 
##   left son=8136 (7 obs) right son=8137 (25 obs)
##   Primary splits:
##       reimbursement2008 < 25510  to the right, improve=3.0153570, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.3731060, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9474206, (0 missing)
##       age               < 72.5   to the right, improve=0.6125000, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.4791667, (0 missing)
## 
## Node number 4069: 9 observations
##   predicted class=B1  expected loss=0.6666667  P(node) =0.00045
##     class counts:     3     1     2     1     2
##    probabilities: 0.333 0.111 0.222 0.111 0.222 
## 
## Node number 4070: 81 observations,    complexity param=0.000380286
##   predicted class=B2  expected loss=0.654321  P(node) =0.00405
##     class counts:    14    28    18    18     3
##    probabilities: 0.173 0.346 0.222 0.222 0.037 
##   left son=8140 (35 obs) right son=8141 (46 obs)
##   Primary splits:
##       age               < 73.5   to the left,  improve=1.8360860, (0 missing)
##       reimbursement2008 < 18450  to the right, improve=1.8267530, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.4464610, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.6743146, (0 missing)
##       bucket2008        < 3.5    to the right, improve=0.6083053, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 18450  to the right, agree=0.741, adj=0.400, (0 split)
##       bucket2008        < 3.5    to the right, agree=0.728, adj=0.371, (0 split)
##       osteoporosis      < 0.5    to the right, agree=0.654, adj=0.200, (0 split)
##       cancer            < 0.5    to the right, agree=0.580, adj=0.029, (0 split)
##       depression        < 0.5    to the left,  agree=0.580, adj=0.029, (0 split)
## 
## Node number 4071: 16 observations
##   predicted class=B4  expected loss=0.5  P(node) =0.0008
##     class counts:     0     2     5     8     1
##    probabilities: 0.000 0.125 0.312 0.500 0.062 
## 
## Node number 4072: 36 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5277778  P(node) =0.0018
##     class counts:     4    17    13     0     2
##    probabilities: 0.111 0.472 0.361 0.000 0.056 
##   left son=8144 (29 obs) right son=8145 (7 obs)
##   Primary splits:
##       reimbursement2008 < 22930  to the right, improve=1.4020250, (0 missing)
##       age               < 70.5   to the left,  improve=1.0793650, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.3754730, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3367677, (0 missing)
##       cancer            < 0.5    to the right, improve=0.2222222, (0 missing)
## 
## Node number 4073: 89 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5842697  P(node) =0.00445
##     class counts:    13    37    19    16     4
##    probabilities: 0.146 0.416 0.213 0.180 0.045 
##   left son=8146 (55 obs) right son=8147 (34 obs)
##   Primary splits:
##       reimbursement2008 < 17640  to the right, improve=1.6152980, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.1922490, (0 missing)
##       age               < 83.5   to the left,  improve=1.1121530, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.0048700, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9641839, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.775, adj=0.412, (0 split)
## 
## Node number 4088: 30 observations
##   predicted class=B2  expected loss=0.3333333  P(node) =0.0015
##     class counts:     2    20     2     4     2
##    probabilities: 0.067 0.667 0.067 0.133 0.067 
## 
## Node number 4089: 17 observations
##   predicted class=B3  expected loss=0.5294118  P(node) =0.00085
##     class counts:     1     5     8     2     1
##    probabilities: 0.059 0.294 0.471 0.118 0.059 
## 
## Node number 4090: 11 observations
##   predicted class=B2  expected loss=0.3636364  P(node) =0.00055
##     class counts:     1     7     2     1     0
##    probabilities: 0.091 0.636 0.182 0.091 0.000 
## 
## Node number 4091: 33 observations,    complexity param=0.0002662002
##   predicted class=B4  expected loss=0.5757576  P(node) =0.00165
##     class counts:     2    12     5    14     0
##    probabilities: 0.061 0.364 0.152 0.424 0.000 
##   left son=8182 (17 obs) right son=8183 (16 obs)
##   Primary splits:
##       arthritis         < 0.5    to the right, improve=1.3990640, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.8990642, (0 missing)
##       reimbursement2008 < 28890  to the right, improve=0.8332194, (0 missing)
##       age               < 66.5   to the right, improve=0.6404040, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3459596, (0 missing)
##   Surrogate splits:
##       age               < 60.5   to the right, agree=0.636, adj=0.250, (0 split)
##       cancer            < 0.5    to the right, agree=0.636, adj=0.250, (0 split)
##       reimbursement2008 < 28890  to the right, agree=0.636, adj=0.250, (0 split)
##       copd              < 0.5    to the right, agree=0.576, adj=0.125, (0 split)
##       depression        < 0.5    to the right, agree=0.576, adj=0.125, (0 split)
## 
## Node number 4092: 26 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.6538462  P(node) =0.0013
##     class counts:     6     9     5     5     1
##    probabilities: 0.231 0.346 0.192 0.192 0.038 
##   left son=8184 (13 obs) right son=8185 (13 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=2.4615380, (0 missing)
##       age               < 77.5   to the left,  improve=0.8995726, (0 missing)
##       reimbursement2008 < 45075  to the right, improve=0.8134615, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6061307, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.4615385, (0 missing)
##   Surrogate splits:
##       age               < 72.5   to the left,  agree=0.615, adj=0.231, (0 split)
##       reimbursement2008 < 41035  to the left,  agree=0.615, adj=0.231, (0 split)
##       bucket2008        < 4.5    to the left,  agree=0.577, adj=0.154, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.538, adj=0.077, (0 split)
##       arthritis         < 0.5    to the left,  agree=0.538, adj=0.077, (0 split)
## 
## Node number 4093: 71 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5774648  P(node) =0.00355
##     class counts:     0    30    12    23     6
##    probabilities: 0.000 0.423 0.169 0.324 0.085 
##   left son=8186 (13 obs) right son=8187 (58 obs)
##   Primary splits:
##       reimbursement2008 < 38625  to the left,  improve=1.735906, (0 missing)
##       age               < 79.5   to the left,  improve=1.085709, (0 missing)
##       bucket2008        < 4.5    to the left,  improve=1.083189, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.081118, (0 missing)
##       cancer            < 0.5    to the right, improve=0.997176, (0 missing)
##   Surrogate splits:
##       age < 86.5   to the right, agree=0.831, adj=0.077, (0 split)
## 
## Node number 4094: 180 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.7  P(node) =0.009
##     class counts:    14    54    53    51     8
##    probabilities: 0.078 0.300 0.294 0.283 0.044 
##   left son=8188 (150 obs) right son=8189 (30 obs)
##   Primary splits:
##       age               < 82.5   to the left,  improve=1.8600000, (0 missing)
##       reimbursement2008 < 101155 to the left,  improve=1.3289020, (0 missing)
##       bucket2008        < 4.5    to the right, improve=1.0857140, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.9828717, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.9785714, (0 missing)
## 
## Node number 4095: 54 observations,    complexity param=0.0001521144
##   predicted class=B4  expected loss=0.5185185  P(node) =0.0027
##     class counts:     4    11    10    26     3
##    probabilities: 0.074 0.204 0.185 0.481 0.056 
##   left son=8190 (39 obs) right son=8191 (15 obs)
##   Primary splits:
##       reimbursement2008 < 35865  to the left,  improve=2.7310540, (0 missing)
##       age               < 83.5   to the right, improve=1.5895620, (0 missing)
##       depression        < 0.5    to the right, improve=1.0054170, (0 missing)
##       cancer            < 0.5    to the right, improve=0.8050992, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4588930, (0 missing)
## 
## Node number 5142: 398 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1758794  P(node) =0.0199
##     class counts:   328    39    26     3     2
##    probabilities: 0.824 0.098 0.065 0.008 0.005 
##   left son=10284 (321 obs) right son=10285 (77 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=0.5824155, (0 missing)
##       age               < 86.5   to the left,  improve=0.5329233, (0 missing)
##       reimbursement2008 < 315    to the left,  improve=0.4958627, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3680496, (0 missing)
##       depression        < 0.5    to the left,  improve=0.2599538, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.809, adj=0.013, (0 split)
## 
## Node number 5143: 32 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.28125  P(node) =0.0016
##     class counts:    23     8     0     1     0
##    probabilities: 0.719 0.250 0.000 0.031 0.000 
##   left son=10286 (10 obs) right son=10287 (22 obs)
##   Primary splits:
##       age               < 83.5   to the right, improve=0.81931820, (0 missing)
##       reimbursement2008 < 485    to the right, improve=0.04142157, (0 missing)
##       ihd               < 0.5    to the right, improve=0.02035714, (0 missing)
## 
## Node number 5766: 51 observations
##   predicted class=B1  expected loss=0.2941176  P(node) =0.00255
##     class counts:    36     6     7     2     0
##    probabilities: 0.706 0.118 0.137 0.039 0.000 
## 
## Node number 5767: 8 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0004
##     class counts:     3     4     1     0     0
##    probabilities: 0.375 0.500 0.125 0.000 0.000 
## 
## Node number 5768: 79 observations
##   predicted class=B1  expected loss=0.2278481  P(node) =0.00395
##     class counts:    61    11     6     1     0
##    probabilities: 0.772 0.139 0.076 0.013 0.000 
## 
## Node number 5769: 30 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.4333333  P(node) =0.0015
##     class counts:    17    10     3     0     0
##    probabilities: 0.567 0.333 0.100 0.000 0.000 
##   left son=11538 (23 obs) right son=11539 (7 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=2.1370600, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.8333333, (0 missing)
##       reimbursement2008 < 1465   to the right, improve=0.7869048, (0 missing)
##       age               < 75.5   to the right, improve=0.3803922, (0 missing)
## 
## Node number 5786: 9 observations
##   predicted class=B1  expected loss=0.2222222  P(node) =0.00045
##     class counts:     7     1     0     1     0
##    probabilities: 0.778 0.111 0.000 0.111 0.000 
## 
## Node number 5787: 11 observations
##   predicted class=B2  expected loss=0.5454545  P(node) =0.00055
##     class counts:     4     5     1     1     0
##    probabilities: 0.364 0.455 0.091 0.091 0.000 
## 
## Node number 5790: 11 observations
##   predicted class=B1  expected loss=0.4545455  P(node) =0.00055
##     class counts:     6     5     0     0     0
##    probabilities: 0.545 0.455 0.000 0.000 0.000 
## 
## Node number 5791: 9 observations
##   predicted class=B2  expected loss=0.3333333  P(node) =0.00045
##     class counts:     3     6     0     0     0
##    probabilities: 0.333 0.667 0.000 0.000 0.000 
## 
## Node number 5898: 10 observations
##   predicted class=B1  expected loss=0.1  P(node) =0.0005
##     class counts:     9     0     1     0     0
##    probabilities: 0.900 0.000 0.100 0.000 0.000 
## 
## Node number 5899: 127 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3149606  P(node) =0.00635
##     class counts:    87    25    12     3     0
##    probabilities: 0.685 0.197 0.094 0.024 0.000 
##   left son=11798 (8 obs) right son=11799 (119 obs)
##   Primary splits:
##       reimbursement2008 < 875    to the left,  improve=0.6516410, (0 missing)
##       depression        < 0.5    to the right, improve=0.4432881, (0 missing)
##       age               < 91     to the right, improve=0.4331536, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1827812, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.1471502, (0 missing)
## 
## Node number 5902: 7 observations
##   predicted class=B1  expected loss=0.5714286  P(node) =0.00035
##     class counts:     3     2     2     0     0
##    probabilities: 0.429 0.286 0.286 0.000 0.000 
## 
## Node number 5903: 13 observations
##   predicted class=B2  expected loss=0.5384615  P(node) =0.00065
##     class counts:     4     6     2     1     0
##    probabilities: 0.308 0.462 0.154 0.077 0.000 
## 
## Node number 6054: 10 observations
##   predicted class=B1  expected loss=0.1  P(node) =0.0005
##     class counts:     9     1     0     0     0
##    probabilities: 0.900 0.100 0.000 0.000 0.000 
## 
## Node number 6055: 115 observations,    complexity param=6.084576e-05
##   predicted class=B1  expected loss=0.3652174  P(node) =0.00575
##     class counts:    73    29    12     0     1
##    probabilities: 0.635 0.252 0.104 0.000 0.009 
##   left son=12110 (36 obs) right son=12111 (79 obs)
##   Primary splits:
##       age               < 73.5   to the right, improve=0.9624839, (0 missing)
##       reimbursement2008 < 1075   to the right, improve=0.7285649, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6802899, (0 missing)
##       kidney            < 0.5    to the right, improve=0.6593008, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.2298137, (0 missing)
##   Surrogate splits:
##       stroke < 0.5    to the right, agree=0.704, adj=0.056, (0 split)
## 
## Node number 6094: 18 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.0009
##     class counts:     8    10     0     0     0
##    probabilities: 0.444 0.556 0.000 0.000 0.000 
## 
## Node number 6095: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     0     3     4     0     0
##    probabilities: 0.000 0.429 0.571 0.000 0.000 
## 
## Node number 6154: 59 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3389831  P(node) =0.00295
##     class counts:    39    15     4     0     1
##    probabilities: 0.661 0.254 0.068 0.000 0.017 
##   left son=12308 (15 obs) right son=12309 (44 obs)
##   Primary splits:
##       reimbursement2008 < 2050   to the right, improve=1.2428860, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.4978711, (0 missing)
##       age               < 47     to the right, improve=0.3049186, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1023175, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the right, agree=0.78, adj=0.133, (0 split)
## 
## Node number 6155: 10 observations
##   predicted class=B1  expected loss=0.6  P(node) =0.0005
##     class counts:     4     4     2     0     0
##    probabilities: 0.400 0.400 0.200 0.000 0.000 
## 
## Node number 6168: 49 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3877551  P(node) =0.00245
##     class counts:    30    15     4     0     0
##    probabilities: 0.612 0.306 0.082 0.000 0.000 
##   left son=12336 (11 obs) right son=12337 (38 obs)
##   Primary splits:
##       reimbursement2008 < 2155   to the right, improve=0.9152427, (0 missing)
##       age               < 71.5   to the right, improve=0.6536797, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2980178, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.2857143, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.0252905, (0 missing)
## 
## Node number 6169: 9 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.00045
##     class counts:     4     5     0     0     0
##    probabilities: 0.444 0.556 0.000 0.000 0.000 
## 
## Node number 6174: 13 observations
##   predicted class=B2  expected loss=0.6153846  P(node) =0.00065
##     class counts:     4     5     3     1     0
##    probabilities: 0.308 0.385 0.231 0.077 0.000 
## 
## Node number 6175: 8 observations
##   predicted class=B4  expected loss=0.625  P(node) =0.0004
##     class counts:     2     1     2     3     0
##    probabilities: 0.250 0.125 0.250 0.375 0.000 
## 
## Node number 6224: 23 observations
##   predicted class=B1  expected loss=0.2173913  P(node) =0.00115
##     class counts:    18     5     0     0     0
##    probabilities: 0.783 0.217 0.000 0.000 0.000 
## 
## Node number 6225: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     2     5     0     0     0
##    probabilities: 0.286 0.714 0.000 0.000 0.000 
## 
## Node number 6362: 45 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.4888889  P(node) =0.00225
##     class counts:    23    13     8     0     1
##    probabilities: 0.511 0.289 0.178 0.000 0.022 
##   left son=12724 (32 obs) right son=12725 (13 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=1.9146370, (0 missing)
##       age               < 78.5   to the left,  improve=1.5873020, (0 missing)
##       reimbursement2008 < 2165   to the right, improve=1.3407410, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.7235888, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6008354, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2895   to the left,  agree=0.778, adj=0.231, (0 split)
## 
## Node number 6363: 60 observations,    complexity param=0.0002028192
##   predicted class=B2  expected loss=0.6  P(node) =0.003
##     class counts:    21    24    13     2     0
##    probabilities: 0.350 0.400 0.217 0.033 0.000 
##   left son=12726 (36 obs) right son=12727 (24 obs)
##   Primary splits:
##       reimbursement2008 < 2215   to the right, improve=2.1944440, (0 missing)
##       age               < 71.5   to the left,  improve=1.3810440, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7444444, (0 missing)
##       copd              < 0.5    to the right, improve=0.2083333, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.1250000, (0 missing)
##   Surrogate splits:
##       age < 73.5   to the left,  agree=0.633, adj=0.083, (0 split)
## 
## Node number 6670: 42 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.5  P(node) =0.0021
##     class counts:    21    18     2     1     0
##    probabilities: 0.500 0.429 0.048 0.024 0.000 
##   left son=13340 (34 obs) right son=13341 (8 obs)
##   Primary splits:
##       reimbursement2008 < 2305   to the left,  improve=0.8284314, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6695992, (0 missing)
##       age               < 79.5   to the left,  improve=0.5952381, (0 missing)
##       kidney            < 0.5    to the right, improve=0.1919192, (0 missing)
##       copd              < 0.5    to the left,  improve=0.1809524, (0 missing)
## 
## Node number 6671: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     2     5     0     1     0
##    probabilities: 0.250 0.625 0.000 0.125 0.000 
## 
## Node number 6680: 19 observations
##   predicted class=B1  expected loss=0.2631579  P(node) =0.00095
##     class counts:    14     3     2     0     0
##    probabilities: 0.737 0.158 0.105 0.000 0.000 
## 
## Node number 6681: 14 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0007
##     class counts:     5     7     1     0     1
##    probabilities: 0.357 0.500 0.071 0.000 0.071 
## 
## Node number 6682: 12 observations
##   predicted class=B1  expected loss=0.4166667  P(node) =0.0006
##     class counts:     7     5     0     0     0
##    probabilities: 0.583 0.417 0.000 0.000 0.000 
## 
## Node number 6683: 18 observations
##   predicted class=B2  expected loss=0.3333333  P(node) =0.0009
##     class counts:     5    12     1     0     0
##    probabilities: 0.278 0.667 0.056 0.000 0.000 
## 
## Node number 6688: 96 observations
##   predicted class=B1  expected loss=0.3020833  P(node) =0.0048
##     class counts:    67    19     7     3     0
##    probabilities: 0.698 0.198 0.073 0.031 0.000 
## 
## Node number 6689: 115 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.4434783  P(node) =0.00575
##     class counts:    64    32    11     7     1
##    probabilities: 0.557 0.278 0.096 0.061 0.009 
##   left son=13378 (20 obs) right son=13379 (95 obs)
##   Primary splits:
##       age               < 60     to the left,  improve=1.2386730, (0 missing)
##       reimbursement2008 < 1735   to the left,  improve=1.2165300, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5300884, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4281976, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1607321, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1585   to the left,  agree=0.843, adj=0.1, (0 split)
## 
## Node number 6704: 88 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5454545  P(node) =0.0044
##     class counts:    36    40     6     5     1
##    probabilities: 0.409 0.455 0.068 0.057 0.011 
##   left son=13408 (55 obs) right son=13409 (33 obs)
##   Primary splits:
##       reimbursement2008 < 1925   to the left,  improve=0.8106061, (0 missing)
##       age               < 66.5   to the right, improve=0.6676136, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.6409091, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.6351931, (0 missing)
##       cancer            < 0.5    to the right, improve=0.5363636, (0 missing)
##   Surrogate splits:
##       alzheimers < 0.5    to the left,  agree=0.659, adj=0.091, (0 split)
##       age        < 72.5   to the left,  agree=0.648, adj=0.061, (0 split)
## 
## Node number 6705: 10 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0005
##     class counts:     5     2     0     3     0
##    probabilities: 0.500 0.200 0.000 0.300 0.000 
## 
## Node number 6708: 16 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0008
##     class counts:     5     8     3     0     0
##    probabilities: 0.312 0.500 0.188 0.000 0.000 
## 
## Node number 6709: 7 observations
##   predicted class=B1  expected loss=0.5714286  P(node) =0.00035
##     class counts:     3     1     3     0     0
##    probabilities: 0.429 0.143 0.429 0.000 0.000 
## 
## Node number 6850: 10 observations
##   predicted class=B1  expected loss=0.2  P(node) =0.0005
##     class counts:     8     0     1     1     0
##    probabilities: 0.800 0.000 0.100 0.100 0.000 
## 
## Node number 6851: 24 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.5  P(node) =0.0012
##     class counts:    12    10     1     1     0
##    probabilities: 0.500 0.417 0.042 0.042 0.000 
##   left son=13702 (14 obs) right son=13703 (10 obs)
##   Primary splits:
##       reimbursement2008 < 1775   to the left,  improve=2.23571400, (0 missing)
##       age               < 65.5   to the left,  improve=0.80714290, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.25000000, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.08333333, (0 missing)
##   Surrogate splits:
##       age          < 47     to the right, agree=0.667, adj=0.2, (0 split)
##       osteoporosis < 0.5    to the left,  agree=0.667, adj=0.2, (0 split)
## 
## Node number 6858: 22 observations
##   predicted class=B2  expected loss=0.5454545  P(node) =0.0011
##     class counts:     4    10     6     2     0
##    probabilities: 0.182 0.455 0.273 0.091 0.000 
## 
## Node number 6859: 7 observations
##   predicted class=B1  expected loss=0.5714286  P(node) =0.00035
##     class counts:     3     0     3     1     0
##    probabilities: 0.429 0.000 0.429 0.143 0.000 
## 
## Node number 6870: 46 observations,    complexity param=0.000253524
##   predicted class=B1  expected loss=0.5869565  P(node) =0.0023
##     class counts:    19    19     8     0     0
##    probabilities: 0.413 0.413 0.174 0.000 0.000 
##   left son=13740 (7 obs) right son=13741 (39 obs)
##   Primary splits:
##       copd              < 0.5    to the right, improve=2.2610290, (0 missing)
##       heart.failure     < 0.5    to the right, improve=2.1976590, (0 missing)
##       reimbursement2008 < 2225   to the left,  improve=1.5721340, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.1052510, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.7791149, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2110   to the left,  agree=0.87, adj=0.143, (0 split)
## 
## Node number 6871: 53 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4150943  P(node) =0.00265
##     class counts:    13    31     8     1     0
##    probabilities: 0.245 0.585 0.151 0.019 0.000 
##   left son=13742 (13 obs) right son=13743 (40 obs)
##   Primary splits:
##       reimbursement2008 < 1795   to the left,  improve=2.1412920, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.3502660, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.1700920, (0 missing)
##       age               < 75.5   to the right, improve=0.9132407, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.4028302, (0 missing)
##   Surrogate splits:
##       age  < 81.5   to the right, agree=0.792, adj=0.154, (0 split)
##       copd < 0.5    to the right, agree=0.792, adj=0.154, (0 split)
## 
## Node number 6934: 41 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5609756  P(node) =0.00205
##     class counts:    18    17     6     0     0
##    probabilities: 0.439 0.415 0.146 0.000 0.000 
##   left son=13868 (30 obs) right son=13869 (11 obs)
##   Primary splits:
##       reimbursement2008 < 2680   to the right, improve=1.4919440, (0 missing)
##       age               < 74.5   to the left,  improve=0.6876399, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.4137873, (0 missing)
##       depression        < 0.5    to the left,  improve=0.2054539, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1305018, (0 missing)
## 
## Node number 6935: 14 observations
##   predicted class=B1  expected loss=0.3571429  P(node) =0.0007
##     class counts:     9     0     2     3     0
##    probabilities: 0.643 0.000 0.143 0.214 0.000 
## 
## Node number 6936: 7 observations
##   predicted class=B1  expected loss=0  P(node) =0.00035
##     class counts:     7     0     0     0     0
##    probabilities: 1.000 0.000 0.000 0.000 0.000 
## 
## Node number 6937: 51 observations,    complexity param=0.0001014096
##   predicted class=B1  expected loss=0.4901961  P(node) =0.00255
##     class counts:    26    11    10     2     2
##    probabilities: 0.510 0.216 0.196 0.039 0.039 
##   left son=13874 (24 obs) right son=13875 (27 obs)
##   Primary splits:
##       reimbursement2008 < 2865   to the left,  improve=1.0511980, (0 missing)
##       age               < 70.5   to the right, improve=0.8104575, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.4304506, (0 missing)
##       kidney            < 0.5    to the right, improve=0.2867201, (0 missing)
##       depression        < 0.5    to the right, improve=0.2437908, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.902, adj=0.792, (0 split)
##       age        < 71.5   to the left,  agree=0.627, adj=0.208, (0 split)
##       kidney     < 0.5    to the right, agree=0.627, adj=0.208, (0 split)
##       copd       < 0.5    to the left,  agree=0.569, adj=0.083, (0 split)
##       depression < 0.5    to the right, agree=0.549, adj=0.042, (0 split)
## 
## Node number 6938: 33 observations,    complexity param=0.0002662002
##   predicted class=B2  expected loss=0.5454545  P(node) =0.00165
##     class counts:    13    15     4     1     0
##    probabilities: 0.394 0.455 0.121 0.030 0.000 
##   left son=13876 (7 obs) right son=13877 (26 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=0.8421578, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7121212, (0 missing)
##       reimbursement2008 < 2665   to the left,  improve=0.5454545, (0 missing)
##       age               < 82.5   to the left,  improve=0.5454545, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.3787879, (0 missing)
## 
## Node number 6939: 13 observations
##   predicted class=B3  expected loss=0.6153846  P(node) =0.00065
##     class counts:     4     3     5     1     0
##    probabilities: 0.308 0.231 0.385 0.077 0.000 
## 
## Node number 6980: 23 observations
##   predicted class=B1  expected loss=0.3478261  P(node) =0.00115
##     class counts:    15     2     3     3     0
##    probabilities: 0.652 0.087 0.130 0.130 0.000 
## 
## Node number 6981: 44 observations,    complexity param=0.000253524
##   predicted class=B1  expected loss=0.5227273  P(node) =0.0022
##     class counts:    21    16     3     4     0
##    probabilities: 0.477 0.364 0.068 0.091 0.000 
##   left son=13962 (23 obs) right son=13963 (21 obs)
##   Primary splits:
##       reimbursement2008 < 2715   to the left,  improve=0.8579898, (0 missing)
##       depression        < 0.5    to the right, improve=0.8196673, (0 missing)
##       age               < 66.5   to the right, improve=0.5631313, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3181818, (0 missing)
##       copd              < 0.5    to the right, improve=0.1969697, (0 missing)
##   Surrogate splits:
##       age        < 66.5   to the right, agree=0.614, adj=0.190, (0 split)
##       depression < 0.5    to the right, agree=0.545, adj=0.048, (0 split)
## 
## Node number 6982: 13 observations
##   predicted class=B1  expected loss=0.3846154  P(node) =0.00065
##     class counts:     8     4     1     0     0
##    probabilities: 0.615 0.308 0.077 0.000 0.000 
## 
## Node number 6983: 45 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.4444444  P(node) =0.00225
##     class counts:    12    25     4     4     0
##    probabilities: 0.267 0.556 0.089 0.089 0.000 
##   left son=13966 (10 obs) right son=13967 (35 obs)
##   Primary splits:
##       reimbursement2008 < 3285   to the right, improve=1.5428570, (0 missing)
##       depression        < 0.5    to the left,  improve=1.2040490, (0 missing)
##       age               < 71     to the right, improve=1.0175680, (0 missing)
##       copd              < 0.5    to the left,  improve=0.9777778, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.3105769, (0 missing)
## 
## Node number 7004: 19 observations
##   predicted class=B2  expected loss=0.5263158  P(node) =0.00095
##     class counts:     4     9     4     2     0
##    probabilities: 0.211 0.474 0.211 0.105 0.000 
## 
## Node number 7005: 20 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.6  P(node) =0.001
##     class counts:     8     3     5     4     0
##    probabilities: 0.400 0.150 0.250 0.200 0.000 
##   left son=14010 (8 obs) right son=14011 (12 obs)
##   Primary splits:
##       reimbursement2008 < 2955   to the left,  improve=1.5500000, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=0.7166667, (0 missing)
##       age               < 79     to the left,  improve=0.4010101, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.80, adj=0.500, (0 split)
##       age        < 58.5   to the left,  agree=0.70, adj=0.250, (0 split)
##       cancer     < 0.5    to the right, agree=0.65, adj=0.125, (0 split)
## 
## Node number 7040: 32 observations,    complexity param=0.0002788764
##   predicted class=B1  expected loss=0.46875  P(node) =0.0016
##     class counts:    17    11     4     0     0
##    probabilities: 0.531 0.344 0.125 0.000 0.000 
##   left son=14080 (18 obs) right son=14081 (14 obs)
##   Primary splits:
##       depression   < 0.5    to the left,  improve=1.3700400, (0 missing)
##       copd         < 0.5    to the left,  improve=1.1875000, (0 missing)
##       diabetes     < 0.5    to the right, improve=0.7541667, (0 missing)
##       osteoporosis < 0.5    to the left,  improve=0.4875000, (0 missing)
##       age          < 68.5   to the left,  improve=0.4494048, (0 missing)
##   Surrogate splits:
##       copd              < 0.5    to the left,  agree=0.688, adj=0.286, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.688, adj=0.286, (0 split)
##       age               < 37.5   to the right, agree=0.625, adj=0.143, (0 split)
##       reimbursement2008 < 2915   to the left,  agree=0.625, adj=0.143, (0 split)
## 
## Node number 7041: 8 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0004
##     class counts:     1     4     1     1     1
##    probabilities: 0.125 0.500 0.125 0.125 0.125 
## 
## Node number 7042: 52 observations
##   predicted class=B2  expected loss=0.4423077  P(node) =0.0026
##     class counts:    15    29     7     1     0
##    probabilities: 0.288 0.558 0.135 0.019 0.000 
## 
## Node number 7043: 12 observations
##   predicted class=B1  expected loss=0.5833333  P(node) =0.0006
##     class counts:     5     3     2     2     0
##    probabilities: 0.417 0.250 0.167 0.167 0.000 
## 
## Node number 7046: 19 observations
##   predicted class=B2  expected loss=0.6315789  P(node) =0.00095
##     class counts:     6     7     6     0     0
##    probabilities: 0.316 0.368 0.316 0.000 0.000 
## 
## Node number 7047: 7 observations
##   predicted class=B3  expected loss=0.1428571  P(node) =0.00035
##     class counts:     1     0     6     0     0
##    probabilities: 0.143 0.000 0.857 0.000 0.000 
## 
## Node number 7194: 79 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4177215  P(node) =0.00395
##     class counts:    46    17    15     1     0
##    probabilities: 0.582 0.215 0.190 0.013 0.000 
##   left son=14388 (32 obs) right son=14389 (47 obs)
##   Primary splits:
##       reimbursement2008 < 4235   to the left,  improve=1.8012560, (0 missing)
##       age               < 70.5   to the right, improve=1.0692790, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.6128692, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4137464, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.3172132, (0 missing)
##   Surrogate splits:
##       age < 76.5   to the right, agree=0.646, adj=0.125, (0 split)
## 
## Node number 7195: 18 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0009
##     class counts:     6     9     2     1     0
##    probabilities: 0.333 0.500 0.111 0.056 0.000 
## 
## Node number 7502: 10 observations
##   predicted class=B1  expected loss=0.6  P(node) =0.0005
##     class counts:     4     3     2     1     0
##    probabilities: 0.400 0.300 0.200 0.100 0.000 
## 
## Node number 7503: 15 observations
##   predicted class=B2  expected loss=0.3333333  P(node) =0.00075
##     class counts:     2    10     2     1     0
##    probabilities: 0.133 0.667 0.133 0.067 0.000 
## 
## Node number 7516: 18 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.0009
##     class counts:     4    10     3     1     0
##    probabilities: 0.222 0.556 0.167 0.056 0.000 
## 
## Node number 7517: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     1     2     3     1     0
##    probabilities: 0.143 0.286 0.429 0.143 0.000 
## 
## Node number 7682: 7 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.00035
##     class counts:     4     3     0     0     0
##    probabilities: 0.571 0.429 0.000 0.000 0.000 
## 
## Node number 7683: 17 observations
##   predicted class=B2  expected loss=0.4117647  P(node) =0.00085
##     class counts:     6    10     1     0     0
##    probabilities: 0.353 0.588 0.059 0.000 0.000 
## 
## Node number 7686: 76 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4868421  P(node) =0.0038
##     class counts:    39    17    18     2     0
##    probabilities: 0.513 0.224 0.237 0.026 0.000 
##   left son=15372 (20 obs) right son=15373 (56 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=1.6184210, (0 missing)
##       reimbursement2008 < 3755   to the left,  improve=1.0173570, (0 missing)
##       age               < 45.5   to the left,  improve=0.4522720, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4366029, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.4050802, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 3515   to the left,  agree=0.763, adj=0.1, (0 split)
## 
## Node number 7687: 28 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0014
##     class counts:     8    14     5     1     0
##    probabilities: 0.286 0.500 0.179 0.036 0.000 
## 
## Node number 7698: 9 observations
##   predicted class=B1  expected loss=0.5555556  P(node) =0.00045
##     class counts:     4     2     0     2     1
##    probabilities: 0.444 0.222 0.000 0.222 0.111 
## 
## Node number 7699: 15 observations
##   predicted class=B2  expected loss=0.4666667  P(node) =0.00075
##     class counts:     2     8     2     3     0
##    probabilities: 0.133 0.533 0.133 0.200 0.000 
## 
## Node number 7712: 11 observations
##   predicted class=B1  expected loss=0.2727273  P(node) =0.00055
##     class counts:     8     0     2     1     0
##    probabilities: 0.727 0.000 0.182 0.091 0.000 
## 
## Node number 7713: 106 observations,    complexity param=0.0003295812
##   predicted class=B1  expected loss=0.5  P(node) =0.0053
##     class counts:    53    35    11     7     0
##    probabilities: 0.500 0.330 0.104 0.066 0.000 
##   left son=15426 (85 obs) right son=15427 (21 obs)
##   Primary splits:
##       reimbursement2008 < 6040   to the right, improve=2.0740760, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.1004920, (0 missing)
##       age               < 83.5   to the left,  improve=0.9104868, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4595413, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.4547943, (0 missing)
## 
## Node number 7714: 13 observations
##   predicted class=B1  expected loss=0.4615385  P(node) =0.00065
##     class counts:     7     5     1     0     0
##    probabilities: 0.538 0.385 0.077 0.000 0.000 
## 
## Node number 7715: 14 observations
##   predicted class=B2  expected loss=0.3571429  P(node) =0.0007
##     class counts:     3     9     1     1     0
##    probabilities: 0.214 0.643 0.071 0.071 0.000 
## 
## Node number 7724: 14 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0007
##     class counts:     7     4     3     0     0
##    probabilities: 0.500 0.286 0.214 0.000 0.000 
## 
## Node number 7725: 47 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.3404255  P(node) =0.00235
##     class counts:     7    31     7     2     0
##    probabilities: 0.149 0.660 0.149 0.043 0.000 
##   left son=15450 (26 obs) right son=15451 (21 obs)
##   Primary splits:
##       age               < 81.5   to the left,  improve=1.7492790, (0 missing)
##       copd              < 0.5    to the left,  improve=1.4122830, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.0571870, (0 missing)
##       reimbursement2008 < 6790   to the right, improve=0.9666891, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.4557060, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 6495   to the right, agree=0.596, adj=0.095, (0 split)
##       copd              < 0.5    to the left,  agree=0.574, adj=0.048, (0 split)
## 
## Node number 7726: 49 observations,    complexity param=0.0004056384
##   predicted class=B2  expected loss=0.6122449  P(node) =0.00245
##     class counts:    15    19     7     7     1
##    probabilities: 0.306 0.388 0.143 0.143 0.020 
##   left son=15452 (38 obs) right son=15453 (11 obs)
##   Primary splits:
##       stroke            < 0.5    to the left,  improve=1.7955280, (0 missing)
##       copd              < 0.5    to the left,  improve=1.3997190, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.3583390, (0 missing)
##       reimbursement2008 < 32725  to the left,  improve=1.0680270, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6528868, (0 missing)
## 
## Node number 7727: 19 observations
##   predicted class=B3  expected loss=0.5263158  P(node) =0.00095
##     class counts:     5     4     9     1     0
##    probabilities: 0.263 0.211 0.474 0.053 0.000 
## 
## Node number 7740: 17 observations
##   predicted class=B1  expected loss=0.4705882  P(node) =0.00085
##     class counts:     9     5     2     1     0
##    probabilities: 0.529 0.294 0.118 0.059 0.000 
## 
## Node number 7741: 20 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.55  P(node) =0.001
##     class counts:     5     9     4     2     0
##    probabilities: 0.250 0.450 0.200 0.100 0.000 
##   left son=15482 (7 obs) right son=15483 (13 obs)
##   Primary splits:
##       age               < 86.5   to the right, improve=0.9747253, (0 missing)
##       reimbursement2008 < 4655   to the right, improve=0.9000000, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8208791, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.3666667, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2274725, (0 missing)
##   Surrogate splits:
##       osteoporosis      < 0.5    to the right, agree=0.8, adj=0.429, (0 split)
##       stroke            < 0.5    to the right, agree=0.7, adj=0.143, (0 split)
##       reimbursement2008 < 4145   to the left,  agree=0.7, adj=0.143, (0 split)
## 
## Node number 7786: 11 observations
##   predicted class=B1  expected loss=0.4545455  P(node) =0.00055
##     class counts:     6     2     3     0     0
##    probabilities: 0.545 0.182 0.273 0.000 0.000 
## 
## Node number 7787: 22 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.5  P(node) =0.0011
##     class counts:     2     7    11     2     0
##    probabilities: 0.091 0.318 0.500 0.091 0.000 
##   left son=15574 (8 obs) right son=15575 (14 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=1.23051900, (0 missing)
##       age               < 67.5   to the left,  improve=1.14242400, (0 missing)
##       reimbursement2008 < 9135   to the left,  improve=0.44242420, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.29004330, (0 missing)
##       depression        < 0.5    to the left,  improve=0.08766234, (0 missing)
##   Surrogate splits:
##       age               < 70.5   to the right, agree=0.727, adj=0.25, (0 split)
##       reimbursement2008 < 6475   to the left,  agree=0.727, adj=0.25, (0 split)
## 
## Node number 7788: 26 observations,    complexity param=7.60572e-05
##   predicted class=B2  expected loss=0.6538462  P(node) =0.0013
##     class counts:     6     9     9     2     0
##    probabilities: 0.231 0.346 0.346 0.077 0.000 
##   left son=15576 (16 obs) right son=15577 (10 obs)
##   Primary splits:
##       age               < 76.5   to the right, improve=0.60576920, (0 missing)
##       reimbursement2008 < 5835   to the left,  improve=0.21769730, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.07692308, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.06107226, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4000   to the right, agree=0.654, adj=0.1, (0 split)
## 
## Node number 7789: 7 observations
##   predicted class=B3  expected loss=0.2857143  P(node) =0.00035
##     class counts:     1     0     5     1     0
##    probabilities: 0.143 0.000 0.714 0.143 0.000 
## 
## Node number 7790: 13 observations
##   predicted class=B2  expected loss=0.1538462  P(node) =0.00065
##     class counts:     0    11     1     1     0
##    probabilities: 0.000 0.846 0.077 0.077 0.000 
## 
## Node number 7791: 17 observations
##   predicted class=B3  expected loss=0.5882353  P(node) =0.00085
##     class counts:     1     6     7     3     0
##    probabilities: 0.059 0.353 0.412 0.176 0.000 
## 
## Node number 7880: 7 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.00035
##     class counts:     5     1     1     0     0
##    probabilities: 0.714 0.143 0.143 0.000 0.000 
## 
## Node number 7881: 52 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.4423077  P(node) =0.0026
##     class counts:    14    29     5     3     1
##    probabilities: 0.269 0.558 0.096 0.058 0.019 
##   left son=15762 (32 obs) right son=15763 (20 obs)
##   Primary splits:
##       reimbursement2008 < 4955   to the right, improve=2.1471150, (0 missing)
##       age               < 74.5   to the right, improve=1.8974360, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.3934850, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7370875, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6891199, (0 missing)
##   Surrogate splits:
##       age < 76.5   to the left,  agree=0.75, adj=0.35, (0 split)
## 
## Node number 7882: 18 observations
##   predicted class=B1  expected loss=0.5555556  P(node) =0.0009
##     class counts:     8     5     3     2     0
##    probabilities: 0.444 0.278 0.167 0.111 0.000 
## 
## Node number 7883: 8 observations
##   predicted class=B2  expected loss=0.625  P(node) =0.0004
##     class counts:     0     3     2     3     0
##    probabilities: 0.000 0.375 0.250 0.375 0.000 
## 
## Node number 7902: 15 observations
##   predicted class=B2  expected loss=0.5333333  P(node) =0.00075
##     class counts:     3     7     5     0     0
##    probabilities: 0.200 0.467 0.333 0.000 0.000 
## 
## Node number 7903: 7 observations
##   predicted class=B3  expected loss=0.1428571  P(node) =0.00035
##     class counts:     0     1     6     0     0
##    probabilities: 0.000 0.143 0.857 0.000 0.000 
## 
## Node number 7912: 30 observations
##   predicted class=B2  expected loss=0.2666667  P(node) =0.0015
##     class counts:     3    22     2     3     0
##    probabilities: 0.100 0.733 0.067 0.100 0.000 
## 
## Node number 7913: 22 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.6363636  P(node) =0.0011
##     class counts:     5     8     8     1     0
##    probabilities: 0.227 0.364 0.364 0.045 0.000 
##   left son=15826 (12 obs) right son=15827 (10 obs)
##   Primary splits:
##       age               < 72.5   to the right, improve=1.7666670, (0 missing)
##       reimbursement2008 < 35585  to the left,  improve=1.1142860, (0 missing)
##       copd              < 0.5    to the right, improve=0.2500000, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.1452991, (0 missing)
##       cancer            < 0.5    to the right, improve=0.1452991, (0 missing)
##   Surrogate splits:
##       copd              < 0.5    to the right, agree=0.636, adj=0.2, (0 split)
##       stroke            < 0.5    to the left,  agree=0.636, adj=0.2, (0 split)
##       reimbursement2008 < 28350  to the left,  agree=0.636, adj=0.2, (0 split)
##       cancer            < 0.5    to the right, agree=0.591, adj=0.1, (0 split)
## 
## Node number 7914: 90 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5222222  P(node) =0.0045
##     class counts:    18    43    20     8     1
##    probabilities: 0.200 0.478 0.222 0.089 0.011 
##   left son=15828 (53 obs) right son=15829 (37 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=1.6669610, (0 missing)
##       reimbursement2008 < 7520   to the left,  improve=1.6335890, (0 missing)
##       age               < 72.5   to the right, improve=1.6301840, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.1552350, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.9296296, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 6155   to the left,  agree=0.644, adj=0.135, (0 split)
##       age               < 70.5   to the right, agree=0.633, adj=0.108, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.611, adj=0.054, (0 split)
##       copd              < 0.5    to the left,  agree=0.600, adj=0.027, (0 split)
## 
## Node number 7915: 74 observations,    complexity param=0.0002281716
##   predicted class=B3  expected loss=0.6486486  P(node) =0.0037
##     class counts:    16    25    26     6     1
##    probabilities: 0.216 0.338 0.351 0.081 0.014 
##   left son=15830 (46 obs) right son=15831 (28 obs)
##   Primary splits:
##       age               < 79.5   to the left,  improve=1.5743660, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.1621620, (0 missing)
##       reimbursement2008 < 10440  to the left,  improve=0.7888245, (0 missing)
##       copd              < 0.5    to the left,  improve=0.7705706, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.6708416, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4315   to the right, agree=0.662, adj=0.107, (0 split)
## 
## Node number 7938: 24 observations,    complexity param=0.0002028192
##   predicted class=B3  expected loss=0.625  P(node) =0.0012
##     class counts:     7     8     9     0     0
##    probabilities: 0.292 0.333 0.375 0.000 0.000 
##   left son=15876 (13 obs) right son=15877 (11 obs)
##   Primary splits:
##       reimbursement2008 < 13055  to the right, improve=1.2453380, (0 missing)
##       copd              < 0.5    to the right, improve=0.7166667, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5833333, (0 missing)
##       age               < 90.5   to the right, improve=0.2864146, (0 missing)
##       stroke            < 0.5    to the right, improve=0.2864146, (0 missing)
##   Surrogate splits:
##       copd          < 0.5    to the right, agree=0.667, adj=0.273, (0 split)
##       age           < 93.5   to the left,  agree=0.625, adj=0.182, (0 split)
##       depression    < 0.5    to the left,  agree=0.625, adj=0.182, (0 split)
##       heart.failure < 0.5    to the right, agree=0.583, adj=0.091, (0 split)
##       stroke        < 0.5    to the right, agree=0.583, adj=0.091, (0 split)
## 
## Node number 7939: 8 observations
##   predicted class=B1  expected loss=0.625  P(node) =0.0004
##     class counts:     3     1     0     2     2
##    probabilities: 0.375 0.125 0.000 0.250 0.250 
## 
## Node number 7948: 169 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.591716  P(node) =0.00845
##     class counts:    43    69    21    31     5
##    probabilities: 0.254 0.408 0.124 0.183 0.030 
##   left son=15896 (24 obs) right son=15897 (145 obs)
##   Primary splits:
##       age               < 75.5   to the right, improve=2.0759710, (0 missing)
##       stroke            < 0.5    to the right, improve=1.4276950, (0 missing)
##       reimbursement2008 < 10940  to the left,  improve=0.9442655, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7626810, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4382567, (0 missing)
## 
## Node number 7949: 8 observations
##   predicted class=B3  expected loss=0.5  P(node) =0.0004
##     class counts:     3     0     4     1     0
##    probabilities: 0.375 0.000 0.500 0.125 0.000 
## 
## Node number 7950: 34 observations,    complexity param=0.0004563432
##   predicted class=B3  expected loss=0.6764706  P(node) =0.0017
##     class counts:     9     8    11     4     2
##    probabilities: 0.265 0.235 0.324 0.118 0.059 
##   left son=15900 (10 obs) right son=15901 (24 obs)
##   Primary splits:
##       copd              < 0.5    to the right, improve=1.4882350, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.2805430, (0 missing)
##       reimbursement2008 < 7950   to the right, improve=0.9321506, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.9321506, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5215686, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 13335  to the right, agree=0.765, adj=0.2, (0 split)
## 
## Node number 7951: 57 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.5789474  P(node) =0.00285
##     class counts:     5    24    13    14     1
##    probabilities: 0.088 0.421 0.228 0.246 0.018 
##   left son=15902 (38 obs) right son=15903 (19 obs)
##   Primary splits:
##       reimbursement2008 < 9695   to the right, improve=2.9298250, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.2396330, (0 missing)
##       depression        < 0.5    to the right, improve=1.0943470, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.9573099, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.9534551, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.807, adj=0.421, (0 split)
##       age        < 78.5   to the right, agree=0.702, adj=0.105, (0 split)
## 
## Node number 7960: 48 observations,    complexity param=0.0003650745
##   predicted class=B2  expected loss=0.4791667  P(node) =0.0024
##     class counts:     9    25     7     6     1
##    probabilities: 0.188 0.521 0.146 0.125 0.021 
##   left son=15920 (25 obs) right son=15921 (23 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=1.7330430, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.2714290, (0 missing)
##       age               < 82.5   to the left,  improve=0.9889435, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8949580, (0 missing)
##       reimbursement2008 < 5780   to the right, improve=0.7500000, (0 missing)
##   Surrogate splits:
##       age               < 82.5   to the right, agree=0.625, adj=0.217, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.604, adj=0.174, (0 split)
##       reimbursement2008 < 4785   to the right, agree=0.604, adj=0.174, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.562, adj=0.087, (0 split)
##       ihd               < 0.5    to the left,  agree=0.562, adj=0.087, (0 split)
## 
## Node number 7961: 162 observations,    complexity param=0.0003650745
##   predicted class=B2  expected loss=0.6419753  P(node) =0.0081
##     class counts:    35    58    40    25     4
##    probabilities: 0.216 0.358 0.247 0.154 0.025 
##   left son=15922 (94 obs) right son=15923 (68 obs)
##   Primary splits:
##       reimbursement2008 < 4895   to the left,  improve=2.1304950, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.6052440, (0 missing)
##       ihd               < 0.5    to the right, improve=1.1317140, (0 missing)
##       age               < 59.5   to the left,  improve=0.9109347, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.8391381, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.623, adj=0.103, (0 split)
##       copd   < 0.5    to the left,  agree=0.599, adj=0.044, (0 split)
##       stroke < 0.5    to the left,  agree=0.586, adj=0.015, (0 split)
## 
## Node number 7962: 17 observations
##   predicted class=B2  expected loss=0.4705882  P(node) =0.00085
##     class counts:     0     9     7     0     1
##    probabilities: 0.000 0.529 0.412 0.000 0.059 
## 
## Node number 7963: 8 observations
##   predicted class=B3  expected loss=0.375  P(node) =0.0004
##     class counts:     1     1     5     1     0
##    probabilities: 0.125 0.125 0.625 0.125 0.000 
## 
## Node number 8018: 29 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.5172414  P(node) =0.00145
##     class counts:    10    14     3     2     0
##    probabilities: 0.345 0.483 0.103 0.069 0.000 
##   left son=16036 (22 obs) right son=16037 (7 obs)
##   Primary splits:
##       reimbursement2008 < 4270   to the left,  improve=1.4746980, (0 missing)
##       age               < 64.5   to the right, improve=0.8383341, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6291413, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4761407, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.3805419, (0 missing)
## 
## Node number 8019: 40 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.45  P(node) =0.002
##     class counts:     4    22    10     3     1
##    probabilities: 0.100 0.550 0.250 0.075 0.025 
##   left son=16038 (31 obs) right son=16039 (9 obs)
##   Primary splits:
##       reimbursement2008 < 3995   to the right, improve=2.3557350, (0 missing)
##       age               < 81.5   to the right, improve=0.8598901, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6281362, (0 missing)
##       depression        < 0.5    to the right, improve=0.4033333, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.2700000, (0 missing)
## 
## Node number 8052: 35 observations
##   predicted class=B2  expected loss=0.6  P(node) =0.00175
##     class counts:     7    14     7     6     1
##    probabilities: 0.200 0.400 0.200 0.171 0.029 
## 
## Node number 8053: 152 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5197368  P(node) =0.0076
##     class counts:    13    73    46    16     4
##    probabilities: 0.086 0.480 0.303 0.105 0.026 
##   left son=16106 (130 obs) right son=16107 (22 obs)
##   Primary splits:
##       reimbursement2008 < 13595  to the left,  improve=1.2442950, (0 missing)
##       age               < 95.5   to the right, improve=0.7711988, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.6892208, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.3316563, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.2600877, (0 missing)
## 
## Node number 8128: 10 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0005
##     class counts:     4     5     1     0     0
##    probabilities: 0.400 0.500 0.100 0.000 0.000 
## 
## Node number 8129: 49 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.6734694  P(node) =0.00245
##     class counts:    16     7    11    15     0
##    probabilities: 0.327 0.143 0.224 0.306 0.000 
##   left son=16258 (41 obs) right son=16259 (8 obs)
##   Primary splits:
##       age               < 86.5   to the left,  improve=1.5618470, (0 missing)
##       depression        < 0.5    to the right, improve=1.5156330, (0 missing)
##       cancer            < 0.5    to the right, improve=1.3809520, (0 missing)
##       reimbursement2008 < 19645  to the right, improve=0.8857143, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.6959034, (0 missing)
## 
## Node number 8136: 7 observations
##   predicted class=B1  expected loss=0.5714286  P(node) =0.00035
##     class counts:     3     1     1     2     0
##    probabilities: 0.429 0.143 0.143 0.286 0.000 
## 
## Node number 8137: 25 observations
##   predicted class=B2  expected loss=0.28  P(node) =0.00125
##     class counts:     1    18     3     1     2
##    probabilities: 0.040 0.720 0.120 0.040 0.080 
## 
## Node number 8140: 35 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5142857  P(node) =0.00175
##     class counts:     5    17     6     5     2
##    probabilities: 0.143 0.486 0.171 0.143 0.057 
##   left son=16280 (28 obs) right son=16281 (7 obs)
##   Primary splits:
##       age               < 60     to the right, improve=2.0285710, (0 missing)
##       reimbursement2008 < 20455  to the left,  improve=1.0914290, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9064713, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5840160, (0 missing)
##       stroke            < 0.5    to the right, improve=0.5047619, (0 missing)
## 
## Node number 8141: 46 observations,    complexity param=0.000380286
##   predicted class=B4  expected loss=0.7173913  P(node) =0.0023
##     class counts:     9    11    12    13     1
##    probabilities: 0.196 0.239 0.261 0.283 0.022 
##   left son=16282 (39 obs) right son=16283 (7 obs)
##   Primary splits:
##       age               < 75.5   to the right, improve=1.7130120, (0 missing)
##       reimbursement2008 < 17795  to the right, improve=1.6235180, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.6115561, (0 missing)
##       bucket2008        < 3.5    to the right, improve=0.3603865, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.2409420, (0 missing)
## 
## Node number 8144: 29 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4482759  P(node) =0.00145
##     class counts:     3    16     9     0     1
##    probabilities: 0.103 0.552 0.310 0.000 0.034 
##   left son=16288 (22 obs) right son=16289 (7 obs)
##   Primary splits:
##       age               < 86     to the left,  improve=0.9046126, (0 missing)
##       reimbursement2008 < 24075  to the left,  improve=0.8900383, (0 missing)
##       cancer            < 0.5    to the right, improve=0.6344828, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5056366, (0 missing)
##       depression        < 0.5    to the right, improve=0.4789272, (0 missing)
## 
## Node number 8145: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     1     1     4     0     1
##    probabilities: 0.143 0.143 0.571 0.000 0.143 
## 
## Node number 8146: 55 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.6  P(node) =0.00275
##     class counts:    13    22     9     9     2
##    probabilities: 0.236 0.400 0.164 0.164 0.036 
##   left son=16292 (20 obs) right son=16293 (35 obs)
##   Primary splits:
##       reimbursement2008 < 18970  to the left,  improve=2.780519, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=2.780519, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.478839, (0 missing)
##       depression        < 0.5    to the left,  improve=1.215758, (0 missing)
##       age               < 83.5   to the right, improve=1.152951, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the left,  agree=1.000, adj=1.00, (0 split)
##       age        < 87     to the right, agree=0.655, adj=0.05, (0 split)
## 
## Node number 8147: 34 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5588235  P(node) =0.0017
##     class counts:     0    15    10     7     2
##    probabilities: 0.000 0.441 0.294 0.206 0.059 
##   left son=16294 (9 obs) right son=16295 (25 obs)
##   Primary splits:
##       age               < 77     to the left,  improve=2.0112420, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.1167850, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.0156860, (0 missing)
##       reimbursement2008 < 16720  to the right, improve=0.6577915, (0 missing)
##       depression        < 0.5    to the left,  improve=0.1471751, (0 missing)
## 
## Node number 8182: 17 observations
##   predicted class=B2  expected loss=0.4705882  P(node) =0.00085
##     class counts:     0     9     1     7     0
##    probabilities: 0.000 0.529 0.059 0.412 0.000 
## 
## Node number 8183: 16 observations
##   predicted class=B4  expected loss=0.5625  P(node) =0.0008
##     class counts:     2     3     4     7     0
##    probabilities: 0.125 0.188 0.250 0.438 0.000 
## 
## Node number 8184: 13 observations
##   predicted class=B1  expected loss=0.5384615  P(node) =0.00065
##     class counts:     6     2     2     2     1
##    probabilities: 0.462 0.154 0.154 0.154 0.077 
## 
## Node number 8185: 13 observations
##   predicted class=B2  expected loss=0.4615385  P(node) =0.00065
##     class counts:     0     7     3     3     0
##    probabilities: 0.000 0.538 0.231 0.231 0.000 
## 
## Node number 8186: 13 observations
##   predicted class=B2  expected loss=0.5384615  P(node) =0.00065
##     class counts:     0     6     5     1     1
##    probabilities: 0.000 0.462 0.385 0.077 0.077 
## 
## Node number 8187: 58 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5862069  P(node) =0.0029
##     class counts:     0    24     7    22     5
##    probabilities: 0.000 0.414 0.121 0.379 0.086 
##   left son=16374 (39 obs) right son=16375 (19 obs)
##   Primary splits:
##       age               < 79.5   to the left,  improve=2.1351850, (0 missing)
##       cancer            < 0.5    to the right, improve=1.3166520, (0 missing)
##       reimbursement2008 < 72235  to the left,  improve=1.1115240, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.7016920, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6656672, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 83625  to the left,  agree=0.724, adj=0.158, (0 split)
##       cancer            < 0.5    to the left,  agree=0.690, adj=0.053, (0 split)
## 
## Node number 8188: 150 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6733333  P(node) =0.0075
##     class counts:    14    49    42    38     7
##    probabilities: 0.093 0.327 0.280 0.253 0.047 
##   left son=16376 (139 obs) right son=16377 (11 obs)
##   Primary splits:
##       reimbursement2008 < 88685  to the left,  improve=1.8771920, (0 missing)
##       age               < 57.5   to the right, improve=1.3581570, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.0064300, (0 missing)
##       bucket2008        < 4.5    to the right, improve=0.9466667, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8913369, (0 missing)
## 
## Node number 8189: 30 observations,    complexity param=0.0003042288
##   predicted class=B4  expected loss=0.5666667  P(node) =0.0015
##     class counts:     0     5    11    13     1
##    probabilities: 0.000 0.167 0.367 0.433 0.033 
##   left son=16378 (9 obs) right son=16379 (21 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=0.7682540, (0 missing)
##       reimbursement2008 < 58390  to the right, improve=0.5971014, (0 missing)
##       depression        < 0.5    to the right, improve=0.5777778, (0 missing)
##       age               < 85.5   to the left,  improve=0.3948963, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2492754, (0 missing)
##   Surrogate splits:
##       age < 87.5   to the right, agree=0.733, adj=0.111, (0 split)
## 
## Node number 8190: 39 observations,    complexity param=0.0001521144
##   predicted class=B4  expected loss=0.6410256  P(node) =0.00195
##     class counts:     4    10     8    14     3
##    probabilities: 0.103 0.256 0.205 0.359 0.077 
##   left son=16380 (27 obs) right son=16381 (12 obs)
##   Primary splits:
##       depression   < 0.5    to the right, improve=1.4245010, (0 missing)
##       age          < 71.5   to the right, improve=1.2051280, (0 missing)
##       osteoporosis < 0.5    to the left,  improve=1.0439950, (0 missing)
##       copd         < 0.5    to the left,  improve=0.8689459, (0 missing)
##       cancer       < 0.5    to the left,  improve=0.6652422, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 35330  to the left,  agree=0.744, adj=0.167, (0 split)
## 
## Node number 8191: 15 observations
##   predicted class=B4  expected loss=0.2  P(node) =0.00075
##     class counts:     0     1     2    12     0
##    probabilities: 0.000 0.067 0.133 0.800 0.000 
## 
## Node number 10284: 321 observations
##   predicted class=B1  expected loss=0.1619938  P(node) =0.01605
##     class counts:   269    28    19     3     2
##    probabilities: 0.838 0.087 0.059 0.009 0.006 
## 
## Node number 10285: 77 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2337662  P(node) =0.00385
##     class counts:    59    11     7     0     0
##    probabilities: 0.766 0.143 0.091 0.000 0.000 
##   left son=20570 (70 obs) right son=20571 (7 obs)
##   Primary splits:
##       age               < 86.5   to the left,  improve=4.6987010, (0 missing)
##       depression        < 0.5    to the left,  improve=1.7558440, (0 missing)
##       reimbursement2008 < 385    to the left,  improve=0.6180762, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.1356976, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1272727, (0 missing)
## 
## Node number 10286: 10 observations
##   predicted class=B1  expected loss=0.1  P(node) =0.0005
##     class counts:     9     1     0     0     0
##    probabilities: 0.900 0.100 0.000 0.000 0.000 
## 
## Node number 10287: 22 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3636364  P(node) =0.0011
##     class counts:    14     7     0     1     0
##    probabilities: 0.636 0.318 0.000 0.045 0.000 
##   left son=20574 (14 obs) right son=20575 (8 obs)
##   Primary splits:
##       age               < 78.5   to the left,  improve=3.13961000, (0 missing)
##       reimbursement2008 < 485    to the right, improve=0.08484848, (0 missing)
##   Surrogate splits:
##       depression < 0.5    to the left,  agree=0.727, adj=0.25, (0 split)
## 
## Node number 11538: 23 observations
##   predicted class=B1  expected loss=0.3478261  P(node) =0.00115
##     class counts:    15     5     3     0     0
##    probabilities: 0.652 0.217 0.130 0.000 0.000 
## 
## Node number 11539: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     2     5     0     0     0
##    probabilities: 0.286 0.714 0.000 0.000 0.000 
## 
## Node number 11798: 8 observations
##   predicted class=B1  expected loss=0.125  P(node) =0.0004
##     class counts:     7     0     1     0     0
##    probabilities: 0.875 0.000 0.125 0.000 0.000 
## 
## Node number 11799: 119 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3277311  P(node) =0.00595
##     class counts:    80    25    11     3     0
##    probabilities: 0.672 0.210 0.092 0.025 0.000 
##   left son=23598 (63 obs) right son=23599 (56 obs)
##   Primary splits:
##       reimbursement2008 < 1125   to the right, improve=0.8342670, (0 missing)
##       depression        < 0.5    to the right, improve=0.6215151, (0 missing)
##       age               < 91     to the right, improve=0.3560924, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.1876751, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1153637, (0 missing)
##   Surrogate splits:
##       age    < 75.5   to the right, agree=0.605, adj=0.161, (0 split)
##       cancer < 0.5    to the left,  agree=0.563, adj=0.071, (0 split)
## 
## Node number 12110: 36 observations,    complexity param=6.084576e-05
##   predicted class=B1  expected loss=0.3888889  P(node) =0.0018
##     class counts:    22    13     1     0     0
##    probabilities: 0.611 0.361 0.028 0.000 0.000 
##   left son=24220 (28 obs) right son=24221 (8 obs)
##   Primary splits:
##       reimbursement2008 < 1005   to the left,  improve=1.2976190, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.9564103, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6806240, (0 missing)
##       age               < 76.5   to the left,  improve=0.2583333, (0 missing)
## 
## Node number 12111: 79 observations,    complexity param=6.084576e-05
##   predicted class=B1  expected loss=0.3544304  P(node) =0.00395
##     class counts:    51    16    11     0     1
##    probabilities: 0.646 0.203 0.139 0.000 0.013 
##   left son=24222 (65 obs) right son=24223 (14 obs)
##   Primary splits:
##       age               < 71.5   to the left,  improve=1.1460840, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8533283, (0 missing)
##       kidney            < 0.5    to the right, improve=0.7541934, (0 missing)
##       depression        < 0.5    to the right, improve=0.7294694, (0 missing)
##       reimbursement2008 < 1075   to the right, improve=0.6940378, (0 missing)
## 
## Node number 12308: 15 observations
##   predicted class=B1  expected loss=0.1333333  P(node) =0.00075
##     class counts:    13     2     0     0     0
##    probabilities: 0.867 0.133 0.000 0.000 0.000 
## 
## Node number 12309: 44 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.4090909  P(node) =0.0022
##     class counts:    26    13     4     0     1
##    probabilities: 0.591 0.295 0.091 0.000 0.023 
##   left son=24618 (16 obs) right son=24619 (28 obs)
##   Primary splits:
##       diabetes          < 0.5    to the right, improve=1.4090910, (0 missing)
##       reimbursement2008 < 1940   to the left,  improve=1.2702020, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.8569674, (0 missing)
##       age               < 52.5   to the right, improve=0.4299242, (0 missing)
##   Surrogate splits:
##       alzheimers < 0.5    to the right, agree=0.75, adj=0.312, (0 split)
## 
## Node number 12336: 11 observations
##   predicted class=B1  expected loss=0.1818182  P(node) =0.00055
##     class counts:     9     2     0     0     0
##    probabilities: 0.818 0.182 0.000 0.000 0.000 
## 
## Node number 12337: 38 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.4473684  P(node) =0.0019
##     class counts:    21    13     4     0     0
##    probabilities: 0.553 0.342 0.105 0.000 0.000 
##   left son=24674 (29 obs) right son=24675 (9 obs)
##   Primary splits:
##       reimbursement2008 < 2020   to the left,  improve=0.85198630, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.59298250, (0 missing)
##       age               < 75.5   to the right, improve=0.46917290, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.21617090, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.04298246, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.789, adj=0.111, (0 split)
## 
## Node number 12724: 32 observations
##   predicted class=B1  expected loss=0.40625  P(node) =0.0016
##     class counts:    19     6     6     0     1
##    probabilities: 0.594 0.188 0.188 0.000 0.031 
## 
## Node number 12725: 13 observations
##   predicted class=B2  expected loss=0.4615385  P(node) =0.00065
##     class counts:     4     7     2     0     0
##    probabilities: 0.308 0.538 0.154 0.000 0.000 
## 
## Node number 12726: 36 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.5555556  P(node) =0.0018
##     class counts:    16    10     8     2     0
##    probabilities: 0.444 0.278 0.222 0.056 0.000 
##   left son=25452 (12 obs) right son=25453 (24 obs)
##   Primary splits:
##       reimbursement2008 < 2400   to the left,  improve=1.3055560, (0 missing)
##       age               < 67.5   to the left,  improve=1.1014790, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8040404, (0 missing)
##       depression        < 0.5    to the right, improve=0.5472222, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.4126984, (0 missing)
##   Surrogate splits:
##       osteoporosis < 0.5    to the right, agree=0.694, adj=0.083, (0 split)
## 
## Node number 12727: 24 observations
##   predicted class=B2  expected loss=0.4166667  P(node) =0.0012
##     class counts:     5    14     5     0     0
##    probabilities: 0.208 0.583 0.208 0.000 0.000 
## 
## Node number 13340: 34 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.4411765  P(node) =0.0017
##     class counts:    19    14     1     0     0
##    probabilities: 0.559 0.412 0.029 0.000 0.000 
##   left son=26680 (7 obs) right son=26681 (27 obs)
##   Primary splits:
##       reimbursement2008 < 2070   to the right, improve=0.96389670, (0 missing)
##       age               < 79.5   to the right, improve=0.48151590, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.41515840, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.41515840, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.06900452, (0 missing)
## 
## Node number 13341: 8 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0004
##     class counts:     2     4     1     1     0
##    probabilities: 0.250 0.500 0.125 0.125 0.000 
## 
## Node number 13378: 20 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.001
##     class counts:    15     5     0     0     0
##    probabilities: 0.750 0.250 0.000 0.000 0.000 
## 
## Node number 13379: 95 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.4842105  P(node) =0.00475
##     class counts:    49    27    11     7     1
##    probabilities: 0.516 0.284 0.116 0.074 0.011 
##   left son=26758 (27 obs) right son=26759 (68 obs)
##   Primary splits:
##       reimbursement2008 < 1735   to the left,  improve=2.2624360, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6768740, (0 missing)
##       age               < 67.5   to the left,  improve=0.6566828, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5342853, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.1812826, (0 missing)
## 
## Node number 13408: 55 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.5272727  P(node) =0.00275
##     class counts:    26    24     2     3     0
##    probabilities: 0.473 0.436 0.036 0.055 0.000 
##   left son=26816 (45 obs) right son=26817 (10 obs)
##   Primary splits:
##       reimbursement2008 < 1865   to the left,  improve=1.1555560, (0 missing)
##       age               < 66.5   to the right, improve=1.0879120, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4500000, (0 missing)
##       kidney            < 0.5    to the right, improve=0.3837209, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.3285714, (0 missing)
## 
## Node number 13409: 33 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5151515  P(node) =0.00165
##     class counts:    10    16     4     2     1
##    probabilities: 0.303 0.485 0.121 0.061 0.030 
##   left son=26818 (7 obs) right son=26819 (26 obs)
##   Primary splits:
##       age               < 72.5   to the right, improve=1.6307030, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.0479800, (0 missing)
##       reimbursement2008 < 1980   to the right, improve=0.9393939, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.8163591, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.5449883, (0 missing)
## 
## Node number 13702: 14 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.0007
##     class counts:    10     4     0     0     0
##    probabilities: 0.714 0.286 0.000 0.000 0.000 
## 
## Node number 13703: 10 observations
##   predicted class=B2  expected loss=0.4  P(node) =0.0005
##     class counts:     2     6     1     1     0
##    probabilities: 0.200 0.600 0.100 0.100 0.000 
## 
## Node number 13740: 7 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.00035
##     class counts:     5     0     2     0     0
##    probabilities: 0.714 0.000 0.286 0.000 0.000 
## 
## Node number 13741: 39 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.5128205  P(node) =0.00195
##     class counts:    14    19     6     0     0
##    probabilities: 0.359 0.487 0.154 0.000 0.000 
##   left son=27482 (15 obs) right son=27483 (24 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the right, improve=2.1782050, (0 missing)
##       reimbursement2008 < 2225   to the left,  improve=0.9035674, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.5156510, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.4871795, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4102564, (0 missing)
##   Surrogate splits:
##       age    < 81.5   to the right, agree=0.692, adj=0.200, (0 split)
##       stroke < 0.5    to the right, agree=0.641, adj=0.067, (0 split)
## 
## Node number 13742: 13 observations
##   predicted class=B1  expected loss=0.4615385  P(node) =0.00065
##     class counts:     7     6     0     0     0
##    probabilities: 0.538 0.462 0.000 0.000 0.000 
## 
## Node number 13743: 40 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.375  P(node) =0.002
##     class counts:     6    25     8     1     0
##    probabilities: 0.150 0.625 0.200 0.025 0.000 
##   left son=27486 (33 obs) right son=27487 (7 obs)
##   Primary splits:
##       age               < 78.5   to the left,  improve=1.5816020, (0 missing)
##       reimbursement2008 < 1955   to the left,  improve=1.1595240, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.1595240, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5166667, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.4983516, (0 missing)
## 
## Node number 13868: 30 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4666667  P(node) =0.0015
##     class counts:    16    11     3     0     0
##    probabilities: 0.533 0.367 0.100 0.000 0.000 
##   left son=27736 (22 obs) right son=27737 (8 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=1.3151520, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7696970, (0 missing)
##       reimbursement2008 < 2845   to the left,  improve=0.6333333, (0 missing)
##       age               < 73.5   to the left,  improve=0.2464555, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.2126984, (0 missing)
##   Surrogate splits:
##       copd              < 0.5    to the left,  agree=0.867, adj=0.500, (0 split)
##       reimbursement2008 < 3015   to the left,  agree=0.867, adj=0.500, (0 split)
##       bucket2008        < 1.5    to the left,  agree=0.833, adj=0.375, (0 split)
## 
## Node number 13869: 11 observations
##   predicted class=B2  expected loss=0.4545455  P(node) =0.00055
##     class counts:     2     6     3     0     0
##    probabilities: 0.182 0.545 0.273 0.000 0.000 
## 
## Node number 13874: 24 observations
##   predicted class=B1  expected loss=0.375  P(node) =0.0012
##     class counts:    15     3     5     0     1
##    probabilities: 0.625 0.125 0.208 0.000 0.042 
## 
## Node number 13875: 27 observations,    complexity param=0.0001014096
##   predicted class=B1  expected loss=0.5925926  P(node) =0.00135
##     class counts:    11     8     5     2     1
##    probabilities: 0.407 0.296 0.185 0.074 0.037 
##   left son=27750 (20 obs) right son=27751 (7 obs)
##   Primary splits:
##       reimbursement2008 < 3040   to the right, improve=1.3798940, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.1664490, (0 missing)
##       age               < 75.5   to the right, improve=0.8791423, (0 missing)
##       depression        < 0.5    to the right, improve=0.1656085, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1481481, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the right, agree=0.926, adj=0.714, (0 split)
## 
## Node number 13876: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     2     5     0     0     0
##    probabilities: 0.286 0.714 0.000 0.000 0.000 
## 
## Node number 13877: 26 observations,    complexity param=0.0002662002
##   predicted class=B1  expected loss=0.5769231  P(node) =0.0013
##     class counts:    11    10     4     1     0
##    probabilities: 0.423 0.385 0.154 0.038 0.000 
##   left son=27754 (12 obs) right son=27755 (14 obs)
##   Primary splits:
##       reimbursement2008 < 2785   to the left,  improve=1.203297, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.040598, (0 missing)
##       age               < 82.5   to the left,  improve=0.707265, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.769, adj=0.500, (0 split)
##       depression < 0.5    to the right, agree=0.615, adj=0.167, (0 split)
##       age        < 81     to the left,  agree=0.577, adj=0.083, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.577, adj=0.083, (0 split)
## 
## Node number 13962: 23 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.5217391  P(node) =0.00115
##     class counts:    10    11     1     1     0
##    probabilities: 0.435 0.478 0.043 0.043 0.000 
##   left son=27924 (9 obs) right son=27925 (14 obs)
##   Primary splits:
##       reimbursement2008 < 2630   to the left,  improve=1.8599030, (0 missing)
##       age               < 71.5   to the right, improve=1.5186340, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7505017, (0 missing)
##   Surrogate splits:
##       age < 71.5   to the left,  agree=0.652, adj=0.111, (0 split)
## 
## Node number 13963: 21 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4761905  P(node) =0.00105
##     class counts:    11     5     2     3     0
##    probabilities: 0.524 0.238 0.095 0.143 0.000 
##   left son=27926 (12 obs) right son=27927 (9 obs)
##   Primary splits:
##       age               < 71.5   to the right, improve=1.2619050, (0 missing)
##       depression        < 0.5    to the right, improve=0.5714286, (0 missing)
##       reimbursement2008 < 2850   to the right, improve=0.1428571, (0 missing)
##   Surrogate splits:
##       copd              < 0.5    to the left,  agree=0.619, adj=0.111, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.619, adj=0.111, (0 split)
##       reimbursement2008 < 2830   to the left,  agree=0.619, adj=0.111, (0 split)
## 
## Node number 13966: 10 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0005
##     class counts:     5     3     1     1     0
##    probabilities: 0.500 0.300 0.100 0.100 0.000 
## 
## Node number 13967: 35 observations
##   predicted class=B2  expected loss=0.3714286  P(node) =0.00175
##     class counts:     7    22     3     3     0
##    probabilities: 0.200 0.629 0.086 0.086 0.000 
## 
## Node number 14010: 8 observations
##   predicted class=B1  expected loss=0.375  P(node) =0.0004
##     class counts:     5     2     1     0     0
##    probabilities: 0.625 0.250 0.125 0.000 0.000 
## 
## Node number 14011: 12 observations
##   predicted class=B3  expected loss=0.6666667  P(node) =0.0006
##     class counts:     3     1     4     4     0
##    probabilities: 0.250 0.083 0.333 0.333 0.000 
## 
## Node number 14080: 18 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0009
##     class counts:    12     4     2     0     0
##    probabilities: 0.667 0.222 0.111 0.000 0.000 
## 
## Node number 14081: 14 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0007
##     class counts:     5     7     2     0     0
##    probabilities: 0.357 0.500 0.143 0.000 0.000 
## 
## Node number 14388: 32 observations
##   predicted class=B1  expected loss=0.4375  P(node) =0.0016
##     class counts:    18    11     2     1     0
##    probabilities: 0.562 0.344 0.062 0.031 0.000 
## 
## Node number 14389: 47 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4042553  P(node) =0.00235
##     class counts:    28     6    13     0     0
##    probabilities: 0.596 0.128 0.277 0.000 0.000 
##   left son=28778 (22 obs) right son=28779 (25 obs)
##   Primary splits:
##       age               < 70.5   to the right, improve=1.1429010, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9358252, (0 missing)
##       reimbursement2008 < 4425   to the right, improve=0.5714819, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.4947017, (0 missing)
##       kidney            < 0.5    to the right, improve=0.3933442, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 5070   to the left,  agree=0.596, adj=0.136, (0 split)
##       alzheimers        < 0.5    to the right, agree=0.574, adj=0.091, (0 split)
##       kidney            < 0.5    to the left,  agree=0.553, adj=0.045, (0 split)
## 
## Node number 15372: 20 observations
##   predicted class=B1  expected loss=0.3  P(node) =0.001
##     class counts:    14     3     2     1     0
##    probabilities: 0.700 0.150 0.100 0.050 0.000 
## 
## Node number 15373: 56 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5535714  P(node) =0.0028
##     class counts:    25    14    16     1     0
##    probabilities: 0.446 0.250 0.286 0.018 0.000 
##   left son=30746 (17 obs) right son=30747 (39 obs)
##   Primary splits:
##       reimbursement2008 < 3745   to the left,  improve=1.6851430, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.1778070, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5569382, (0 missing)
##       age               < 53.5   to the right, improve=0.4621212, (0 missing)
##       depression        < 0.5    to the left,  improve=0.1055556, (0 missing)
##   Surrogate splits:
##       age < 69.5   to the right, agree=0.714, adj=0.059, (0 split)
## 
## Node number 15426: 85 observations,    complexity param=0.0003295812
##   predicted class=B1  expected loss=0.4588235  P(node) =0.00425
##     class counts:    46    28    10     1     0
##    probabilities: 0.541 0.329 0.118 0.012 0.000 
##   left son=30852 (76 obs) right son=30853 (9 obs)
##   Primary splits:
##       reimbursement2008 < 29020  to the left,  improve=1.3666320, (0 missing)
##       age               < 82.5   to the left,  improve=0.8676149, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4882353, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.3426025, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.3141176, (0 missing)
##   Surrogate splits:
##       bucket2008 < 4.5    to the left,  agree=0.918, adj=0.222, (0 split)
## 
## Node number 15427: 21 observations,    complexity param=0.0003295812
##   predicted class=B1  expected loss=0.6666667  P(node) =0.00105
##     class counts:     7     7     1     6     0
##    probabilities: 0.333 0.333 0.048 0.286 0.000 
##   left son=30854 (13 obs) right son=30855 (8 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=1.2060440, (0 missing)
##       reimbursement2008 < 5580   to the left,  improve=0.7637363, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4285714, (0 missing)
##       age               < 79.5   to the right, improve=0.2936508, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1428571, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 5580   to the left,  agree=0.810, adj=0.500, (0 split)
##       stroke            < 0.5    to the left,  agree=0.714, adj=0.250, (0 split)
##       age               < 83.5   to the left,  agree=0.667, adj=0.125, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.667, adj=0.125, (0 split)
## 
## Node number 15450: 26 observations
##   predicted class=B2  expected loss=0.1923077  P(node) =0.0013
##     class counts:     3    21     2     0     0
##    probabilities: 0.115 0.808 0.077 0.000 0.000 
## 
## Node number 15451: 21 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5238095  P(node) =0.00105
##     class counts:     4    10     5     2     0
##    probabilities: 0.190 0.476 0.238 0.095 0.000 
##   left son=30902 (10 obs) right son=30903 (11 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.0406930, (0 missing)
##       reimbursement2008 < 10445  to the right, improve=0.2380952, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.1861472, (0 missing)
##       age               < 86.5   to the right, improve=0.1721612, (0 missing)
##   Surrogate splits:
##       age               < 86.5   to the right, agree=0.714, adj=0.4, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.619, adj=0.2, (0 split)
##       reimbursement2008 < 5600   to the left,  agree=0.619, adj=0.2, (0 split)
## 
## Node number 15452: 38 observations,    complexity param=0.0004056384
##   predicted class=B1  expected loss=0.6052632  P(node) =0.0019
##     class counts:    15    13     5     5     0
##    probabilities: 0.395 0.342 0.132 0.132 0.000 
##   left son=30904 (26 obs) right son=30905 (12 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the right, improve=1.3927130, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.2562660, (0 missing)
##       copd              < 0.5    to the left,  improve=1.1773280, (0 missing)
##       age               < 78.5   to the right, improve=0.7975822, (0 missing)
##       reimbursement2008 < 21895  to the left,  improve=0.5716817, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 7780   to the right, agree=0.763, adj=0.250, (0 split)
##       bucket2008        < 2.5    to the right, agree=0.737, adj=0.167, (0 split)
## 
## Node number 15453: 11 observations
##   predicted class=B2  expected loss=0.4545455  P(node) =0.00055
##     class counts:     0     6     2     2     1
##    probabilities: 0.000 0.545 0.182 0.182 0.091 
## 
## Node number 15482: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     2     2     3     0     0
##    probabilities: 0.286 0.286 0.429 0.000 0.000 
## 
## Node number 15483: 13 observations
##   predicted class=B2  expected loss=0.4615385  P(node) =0.00065
##     class counts:     3     7     1     2     0
##    probabilities: 0.231 0.538 0.077 0.154 0.000 
## 
## Node number 15574: 8 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0004
##     class counts:     1     4     2     1     0
##    probabilities: 0.125 0.500 0.250 0.125 0.000 
## 
## Node number 15575: 14 observations
##   predicted class=B3  expected loss=0.3571429  P(node) =0.0007
##     class counts:     1     3     9     1     0
##    probabilities: 0.071 0.214 0.643 0.071 0.000 
## 
## Node number 15576: 16 observations
##   predicted class=B3  expected loss=0.625  P(node) =0.0008
##     class counts:     5     5     6     0     0
##    probabilities: 0.312 0.312 0.375 0.000 0.000 
## 
## Node number 15577: 10 observations
##   predicted class=B2  expected loss=0.6  P(node) =0.0005
##     class counts:     1     4     3     2     0
##    probabilities: 0.100 0.400 0.300 0.200 0.000 
## 
## Node number 15762: 32 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5625  P(node) =0.0016
##     class counts:    12    14     3     2     1
##    probabilities: 0.375 0.438 0.094 0.062 0.031 
##   left son=31524 (8 obs) right son=31525 (24 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=2.0208330, (0 missing)
##       reimbursement2008 < 5625   to the left,  improve=1.1806370, (0 missing)
##       age               < 67     to the left,  improve=0.8541667, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6943627, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6344697, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 5120   to the left,  agree=0.781, adj=0.125, (0 split)
## 
## Node number 15763: 20 observations
##   predicted class=B2  expected loss=0.25  P(node) =0.001
##     class counts:     2    15     2     1     0
##    probabilities: 0.100 0.750 0.100 0.050 0.000 
## 
## Node number 15826: 12 observations
##   predicted class=B2  expected loss=0.4166667  P(node) =0.0006
##     class counts:     2     7     3     0     0
##    probabilities: 0.167 0.583 0.250 0.000 0.000 
## 
## Node number 15827: 10 observations
##   predicted class=B3  expected loss=0.5  P(node) =0.0005
##     class counts:     3     1     5     1     0
##    probabilities: 0.300 0.100 0.500 0.100 0.000 
## 
## Node number 15828: 53 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5283019  P(node) =0.00265
##     class counts:    14    25     7     6     1
##    probabilities: 0.264 0.472 0.132 0.113 0.019 
##   left son=31656 (10 obs) right son=31657 (43 obs)
##   Primary splits:
##       copd              < 0.5    to the right, improve=1.6914440, (0 missing)
##       age               < 84.5   to the right, improve=1.2423480, (0 missing)
##       reimbursement2008 < 4140   to the right, improve=1.2035630, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.4599632, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.4325067, (0 missing)
##   Surrogate splits:
##       age < 85.5   to the right, agree=0.83, adj=0.1, (0 split)
## 
## Node number 15829: 37 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5135135  P(node) =0.00185
##     class counts:     4    18    13     2     0
##    probabilities: 0.108 0.486 0.351 0.054 0.000 
##   left son=31658 (15 obs) right son=31659 (22 obs)
##   Primary splits:
##       age               < 74.5   to the right, improve=2.4139230, (0 missing)
##       reimbursement2008 < 9285   to the left,  improve=0.9525955, (0 missing)
##       copd              < 0.5    to the right, improve=0.9323379, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6526177, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.4084271, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 8600   to the right, agree=0.649, adj=0.133, (0 split)
##       cancer            < 0.5    to the right, agree=0.622, adj=0.067, (0 split)
## 
## Node number 15830: 46 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5869565  P(node) =0.0023
##     class counts:     7    19    18     2     0
##    probabilities: 0.152 0.413 0.391 0.043 0.000 
##   left son=31660 (10 obs) right son=31661 (36 obs)
##   Primary splits:
##       reimbursement2008 < 5620   to the left,  improve=1.5787440, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.4489460, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.2212840, (0 missing)
##       age               < 72.5   to the left,  improve=0.6469979, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5652174, (0 missing)
## 
## Node number 15831: 28 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.6785714  P(node) =0.0014
##     class counts:     9     6     8     4     1
##    probabilities: 0.321 0.214 0.286 0.143 0.036 
##   left son=31662 (9 obs) right son=31663 (19 obs)
##   Primary splits:
##       age               < 84.5   to the left,  improve=2.6829570, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.8841270, (0 missing)
##       reimbursement2008 < 9375   to the left,  improve=1.4047620, (0 missing)
##       copd              < 0.5    to the left,  improve=1.1730160, (0 missing)
##       ihd               < 0.5    to the right, improve=0.6785714, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 11245  to the right, agree=0.75, adj=0.222, (0 split)
## 
## Node number 15876: 13 observations
##   predicted class=B1  expected loss=0.5384615  P(node) =0.00065
##     class counts:     6     3     4     0     0
##    probabilities: 0.462 0.231 0.308 0.000 0.000 
## 
## Node number 15877: 11 observations
##   predicted class=B2  expected loss=0.5454545  P(node) =0.00055
##     class counts:     1     5     5     0     0
##    probabilities: 0.091 0.455 0.455 0.000 0.000 
## 
## Node number 15896: 24 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.5416667  P(node) =0.0012
##     class counts:    11     6     1     5     1
##    probabilities: 0.458 0.250 0.042 0.208 0.042 
##   left son=31792 (10 obs) right son=31793 (14 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.3904760, (0 missing)
##       reimbursement2008 < 8475   to the left,  improve=0.7083333, (0 missing)
##       age               < 76.5   to the left,  improve=0.7047619, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7047619, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.5291375, (0 missing)
##   Surrogate splits:
##       alzheimers        < 0.5    to the right, agree=0.708, adj=0.3, (0 split)
##       depression        < 0.5    to the right, agree=0.667, adj=0.2, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.667, adj=0.2, (0 split)
##       reimbursement2008 < 8545   to the left,  agree=0.625, adj=0.1, (0 split)
## 
## Node number 15897: 145 observations,    complexity param=0.0002738059
##   predicted class=B2  expected loss=0.5655172  P(node) =0.00725
##     class counts:    32    63    20    26     4
##    probabilities: 0.221 0.434 0.138 0.179 0.028 
##   left son=31794 (18 obs) right son=31795 (127 obs)
##   Primary splits:
##       stroke            < 0.5    to the right, improve=1.3643170, (0 missing)
##       age               < 69.5   to the right, improve=1.3391670, (0 missing)
##       reimbursement2008 < 12310  to the left,  improve=1.0866570, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7151354, (0 missing)
##       depression        < 0.5    to the right, improve=0.5171751, (0 missing)
## 
## Node number 15900: 10 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0005
##     class counts:     2     5     2     0     1
##    probabilities: 0.200 0.500 0.200 0.000 0.100 
## 
## Node number 15901: 24 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.625  P(node) =0.0012
##     class counts:     7     3     9     4     1
##    probabilities: 0.292 0.125 0.375 0.167 0.042 
##   left son=31802 (17 obs) right son=31803 (7 obs)
##   Primary splits:
##       cancer            < 0.5    to the left,  improve=1.3823530, (0 missing)
##       reimbursement2008 < 10140  to the left,  improve=1.3181820, (0 missing)
##       depression        < 0.5    to the left,  improve=0.3333333, (0 missing)
##       age               < 82.5   to the left,  improve=0.3000000, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1153846, (0 missing)
##   Surrogate splits:
##       age               < 78.5   to the right, agree=0.792, adj=0.286, (0 split)
##       reimbursement2008 < 12480  to the left,  agree=0.750, adj=0.143, (0 split)
## 
## Node number 15902: 38 observations,    complexity param=7.60572e-05
##   predicted class=B2  expected loss=0.4736842  P(node) =0.0019
##     class counts:     3    20    10     5     0
##    probabilities: 0.079 0.526 0.263 0.132 0.000 
##   left son=31804 (23 obs) right son=31805 (15 obs)
##   Primary splits:
##       reimbursement2008 < 13070  to the left,  improve=1.5183830, (0 missing)
##       depression        < 0.5    to the right, improve=0.6842105, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5789474, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.3616541, (0 missing)
##       age               < 81.5   to the left,  improve=0.3395253, (0 missing)
##   Surrogate splits:
##       depression < 0.5    to the right, agree=0.632, adj=0.067, (0 split)
## 
## Node number 15903: 19 observations
##   predicted class=B4  expected loss=0.5263158  P(node) =0.00095
##     class counts:     2     4     3     9     1
##    probabilities: 0.105 0.211 0.158 0.474 0.053 
## 
## Node number 15920: 25 observations,    complexity param=0.0003650745
##   predicted class=B2  expected loss=0.6  P(node) =0.00125
##     class counts:     8    10     3     3     1
##    probabilities: 0.320 0.400 0.120 0.120 0.040 
##   left son=31840 (12 obs) right son=31841 (13 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the right, improve=2.974872, (0 missing)
##       reimbursement2008 < 5050   to the right, improve=2.154359, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.596667, (0 missing)
##       copd              < 0.5    to the left,  improve=1.546667, (0 missing)
##       age               < 84.5   to the left,  improve=0.654359, (0 missing)
##   Surrogate splits:
##       age               < 83.5   to the left,  agree=0.64, adj=0.250, (0 split)
##       copd              < 0.5    to the left,  agree=0.64, adj=0.250, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.64, adj=0.250, (0 split)
##       reimbursement2008 < 5050   to the left,  agree=0.64, adj=0.250, (0 split)
##       cancer            < 0.5    to the right, agree=0.60, adj=0.167, (0 split)
## 
## Node number 15921: 23 observations
##   predicted class=B2  expected loss=0.3478261  P(node) =0.00115
##     class counts:     1    15     4     3     0
##    probabilities: 0.043 0.652 0.174 0.130 0.000 
## 
## Node number 15922: 94 observations,    complexity param=0.0003650745
##   predicted class=B2  expected loss=0.5744681  P(node) =0.0047
##     class counts:    22    40    17    13     2
##    probabilities: 0.234 0.426 0.181 0.138 0.021 
##   left son=31844 (47 obs) right son=31845 (47 obs)
##   Primary splits:
##       reimbursement2008 < 4080   to the left,  improve=2.3617020, (0 missing)
##       age               < 59.5   to the left,  improve=0.9410374, (0 missing)
##       copd              < 0.5    to the right, improve=0.7460624, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.7348936, (0 missing)
##       ihd               < 0.5    to the right, improve=0.5315420, (0 missing)
##   Surrogate splits:
##       depression    < 0.5    to the left,  agree=0.638, adj=0.277, (0 split)
##       copd          < 0.5    to the right, agree=0.628, adj=0.255, (0 split)
##       cancer        < 0.5    to the left,  agree=0.564, adj=0.128, (0 split)
##       age           < 59.5   to the left,  agree=0.553, adj=0.106, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.553, adj=0.106, (0 split)
## 
## Node number 15923: 68 observations,    complexity param=0.0003650745
##   predicted class=B3  expected loss=0.6617647  P(node) =0.0034
##     class counts:    13    18    23    12     2
##    probabilities: 0.191 0.265 0.338 0.176 0.029 
##   left son=31846 (39 obs) right son=31847 (29 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=2.0284240, (0 missing)
##       reimbursement2008 < 5310   to the left,  improve=1.4514850, (0 missing)
##       depression        < 0.5    to the right, improve=1.3449950, (0 missing)
##       age               < 76.5   to the right, improve=1.1528720, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.6729055, (0 missing)
##   Surrogate splits:
##       age               < 75.5   to the right, agree=0.632, adj=0.138, (0 split)
##       stroke            < 0.5    to the left,  agree=0.618, adj=0.103, (0 split)
##       reimbursement2008 < 5600   to the left,  agree=0.618, adj=0.103, (0 split)
##       ihd               < 0.5    to the right, agree=0.588, adj=0.034, (0 split)
## 
## Node number 16036: 22 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.4545455  P(node) =0.0011
##     class counts:     9    12     1     0     0
##    probabilities: 0.409 0.545 0.045 0.000 0.000 
##   left son=32072 (7 obs) right son=32073 (15 obs)
##   Primary splits:
##       reimbursement2008 < 3905   to the left,  improve=1.0606060, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9772727, (0 missing)
##       age               < 70     to the right, improve=0.4701299, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.1201299, (0 missing)
## 
## Node number 16037: 7 observations
##   predicted class=B2  expected loss=0.7142857  P(node) =0.00035
##     class counts:     1     2     2     2     0
##    probabilities: 0.143 0.286 0.286 0.286 0.000 
## 
## Node number 16038: 31 observations
##   predicted class=B2  expected loss=0.3548387  P(node) =0.00155
##     class counts:     3    20     5     2     1
##    probabilities: 0.097 0.645 0.161 0.065 0.032 
## 
## Node number 16039: 9 observations
##   predicted class=B3  expected loss=0.4444444  P(node) =0.00045
##     class counts:     1     2     5     1     0
##    probabilities: 0.111 0.222 0.556 0.111 0.000 
## 
## Node number 16106: 130 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5  P(node) =0.0065
##     class counts:    13    65    36    14     2
##    probabilities: 0.100 0.500 0.277 0.108 0.015 
##   left son=32212 (52 obs) right son=32213 (78 obs)
##   Primary splits:
##       reimbursement2008 < 10630  to the right, improve=1.0128210, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.7109522, (0 missing)
##       age               < 95.5   to the right, improve=0.6226356, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.4532726, (0 missing)
##       depression        < 0.5    to the left,  improve=0.3446886, (0 missing)
##   Surrogate splits:
##       age < 96.5   to the right, agree=0.608, adj=0.019, (0 split)
## 
## Node number 16107: 22 observations,    complexity param=0.0001521144
##   predicted class=B3  expected loss=0.5454545  P(node) =0.0011
##     class counts:     0     8    10     2     2
##    probabilities: 0.000 0.364 0.455 0.091 0.091 
##   left son=32214 (14 obs) right son=32215 (8 obs)
##   Primary splits:
##       reimbursement2008 < 14005  to the right, improve=1.5032470, (0 missing)
##       age               < 70     to the left,  improve=0.8142968, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.6151515, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5484848, (0 missing)
##       depression        < 0.5    to the right, improve=0.4318182, (0 missing)
##   Surrogate splits:
##       stroke < 0.5    to the left,  agree=0.682, adj=0.125, (0 split)
## 
## Node number 16258: 41 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.6341463  P(node) =0.00205
##     class counts:    15     7     9    10     0
##    probabilities: 0.366 0.171 0.220 0.244 0.000 
##   left son=32516 (23 obs) right son=32517 (18 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=2.0715210, (0 missing)
##       age               < 74.5   to the right, improve=1.6679890, (0 missing)
##       cancer            < 0.5    to the right, improve=1.0314710, (0 missing)
##       reimbursement2008 < 24805  to the right, improve=0.9024390, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4716698, (0 missing)
##   Surrogate splits:
##       age               < 78.5   to the left,  agree=0.610, adj=0.111, (0 split)
##       reimbursement2008 < 24395  to the left,  agree=0.610, adj=0.111, (0 split)
##       alzheimers        < 0.5    to the right, agree=0.585, adj=0.056, (0 split)
## 
## Node number 16259: 8 observations
##   predicted class=B4  expected loss=0.375  P(node) =0.0004
##     class counts:     1     0     2     5     0
##    probabilities: 0.125 0.000 0.250 0.625 0.000 
## 
## Node number 16280: 28 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.0014
##     class counts:     5    16     3     3     1
##    probabilities: 0.179 0.571 0.107 0.107 0.036 
## 
## Node number 16281: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     0     1     3     2     1
##    probabilities: 0.000 0.143 0.429 0.286 0.143 
## 
## Node number 16282: 39 observations,    complexity param=0.000380286
##   predicted class=B2  expected loss=0.7179487  P(node) =0.00195
##     class counts:     9    11     9     9     1
##    probabilities: 0.231 0.282 0.231 0.231 0.026 
##   left son=32564 (10 obs) right son=32565 (29 obs)
##   Primary splits:
##       age               < 80     to the left,  improve=1.7168880, (0 missing)
##       reimbursement2008 < 17795  to the right, improve=0.9267399, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.8587676, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4467399, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3426385, (0 missing)
##   Surrogate splits:
##       heart.failure < 0.5    to the left,  agree=0.769, adj=0.1, (0 split)
## 
## Node number 16283: 7 observations
##   predicted class=B4  expected loss=0.4285714  P(node) =0.00035
##     class counts:     0     0     3     4     0
##    probabilities: 0.000 0.000 0.429 0.571 0.000 
## 
## Node number 16288: 22 observations
##   predicted class=B2  expected loss=0.3636364  P(node) =0.0011
##     class counts:     2    14     6     0     0
##    probabilities: 0.091 0.636 0.273 0.000 0.000 
## 
## Node number 16289: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     1     2     3     0     1
##    probabilities: 0.143 0.286 0.429 0.000 0.143 
## 
## Node number 16292: 20 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.55  P(node) =0.001
##     class counts:     9     4     4     3     0
##    probabilities: 0.450 0.200 0.200 0.150 0.000 
##   left son=32584 (10 obs) right son=32585 (10 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=1.9000000, (0 missing)
##       copd              < 0.5    to the left,  improve=1.8166670, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.2186810, (0 missing)
##       reimbursement2008 < 18105  to the left,  improve=0.8166667, (0 missing)
##       age               < 79     to the left,  improve=0.5000000, (0 missing)
##   Surrogate splits:
##       alzheimers        < 0.5    to the right, agree=0.65, adj=0.3, (0 split)
##       reimbursement2008 < 18235  to the left,  agree=0.65, adj=0.3, (0 split)
##       age               < 93.5   to the right, agree=0.60, adj=0.2, (0 split)
##       copd              < 0.5    to the right, agree=0.60, adj=0.2, (0 split)
##       cancer            < 0.5    to the left,  agree=0.55, adj=0.1, (0 split)
## 
## Node number 16293: 35 observations
##   predicted class=B2  expected loss=0.4857143  P(node) =0.00175
##     class counts:     4    18     5     6     2
##    probabilities: 0.114 0.514 0.143 0.171 0.057 
## 
## Node number 16294: 9 observations
##   predicted class=B2  expected loss=0.2222222  P(node) =0.00045
##     class counts:     0     7     2     0     0
##    probabilities: 0.000 0.778 0.222 0.000 0.000 
## 
## Node number 16295: 25 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.68  P(node) =0.00125
##     class counts:     0     8     8     7     2
##    probabilities: 0.000 0.320 0.320 0.280 0.080 
##   left son=32590 (10 obs) right son=32591 (15 obs)
##   Primary splits:
##       age               < 82.5   to the left,  improve=1.0933330, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.8933333, (0 missing)
##       reimbursement2008 < 16595  to the right, improve=0.6171429, (0 missing)
##       depression        < 0.5    to the left,  improve=0.1885714, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.1276471, (0 missing)
##   Surrogate splits:
##       cancer            < 0.5    to the right, agree=0.68, adj=0.2, (0 split)
##       copd              < 0.5    to the right, agree=0.68, adj=0.2, (0 split)
##       reimbursement2008 < 17140  to the right, agree=0.68, adj=0.2, (0 split)
## 
## Node number 16374: 39 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5128205  P(node) =0.00195
##     class counts:     0    19     3    17     0
##    probabilities: 0.000 0.487 0.077 0.436 0.000 
##   left son=32748 (26 obs) right son=32749 (13 obs)
##   Primary splits:
##       age               < 63.5   to the right, improve=0.9487179, (0 missing)
##       reimbursement2008 < 43555  to the left,  improve=0.6509512, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5692308, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.3145206, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2601728, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 40920  to the right, agree=0.744, adj=0.231, (0 split)
## 
## Node number 16375: 19 observations
##   predicted class=B2  expected loss=0.7368421  P(node) =0.00095
##     class counts:     0     5     4     5     5
##    probabilities: 0.000 0.263 0.211 0.263 0.263 
## 
## Node number 16376: 139 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6546763  P(node) =0.00695
##     class counts:    14    48    36    36     5
##    probabilities: 0.101 0.345 0.259 0.259 0.036 
##   left son=32752 (7 obs) right son=32753 (132 obs)
##   Primary splits:
##       reimbursement2008 < 79435  to the right, improve=1.587483, (0 missing)
##       age               < 68.5   to the right, improve=1.331578, (0 missing)
##       bucket2008        < 4.5    to the right, improve=1.092884, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.060491, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.026367, (0 missing)
## 
## Node number 16377: 11 observations
##   predicted class=B3  expected loss=0.4545455  P(node) =0.00055
##     class counts:     0     1     6     2     2
##    probabilities: 0.000 0.091 0.545 0.182 0.182 
## 
## Node number 16378: 9 observations
##   predicted class=B3  expected loss=0.5555556  P(node) =0.00045
##     class counts:     0     2     4     2     1
##    probabilities: 0.000 0.222 0.444 0.222 0.111 
## 
## Node number 16379: 21 observations,    complexity param=0.0001521144
##   predicted class=B4  expected loss=0.4761905  P(node) =0.00105
##     class counts:     0     3     7    11     0
##    probabilities: 0.000 0.143 0.333 0.524 0.000 
##   left son=32758 (10 obs) right son=32759 (11 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=0.8580087, (0 missing)
##       age               < 85.5   to the left,  improve=0.5317460, (0 missing)
##       reimbursement2008 < 49045  to the left,  improve=0.4398268, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.2261905, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.1904762, (0 missing)
##   Surrogate splits:
##       cancer            < 0.5    to the right, agree=0.810, adj=0.6, (0 split)
##       arthritis         < 0.5    to the right, agree=0.667, adj=0.3, (0 split)
##       reimbursement2008 < 42665  to the left,  agree=0.619, adj=0.2, (0 split)
##       age               < 83.5   to the left,  agree=0.571, adj=0.1, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.571, adj=0.1, (0 split)
## 
## Node number 16380: 27 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.7037037  P(node) =0.00135
##     class counts:     2     8     8     8     1
##    probabilities: 0.074 0.296 0.296 0.296 0.037 
##   left son=32760 (19 obs) right son=32761 (8 obs)
##   Primary splits:
##       age               < 70     to the right, improve=0.9800195, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.9370370, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.8741582, (0 missing)
##       reimbursement2008 < 34375  to the left,  improve=0.5389978, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.3968855, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.741, adj=0.125, (0 split)
## 
## Node number 16381: 12 observations
##   predicted class=B4  expected loss=0.5  P(node) =0.0006
##     class counts:     2     2     0     6     2
##    probabilities: 0.167 0.167 0.000 0.500 0.167 
## 
## Node number 20570: 70 observations
##   predicted class=B1  expected loss=0.1714286  P(node) =0.0035
##     class counts:    58     7     5     0     0
##    probabilities: 0.829 0.100 0.071 0.000 0.000 
## 
## Node number 20571: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     1     4     2     0     0
##    probabilities: 0.143 0.571 0.286 0.000 0.000 
## 
## Node number 20574: 14 observations
##   predicted class=B1  expected loss=0.1428571  P(node) =0.0007
##     class counts:    12     2     0     0     0
##    probabilities: 0.857 0.143 0.000 0.000 0.000 
## 
## Node number 20575: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     2     5     0     1     0
##    probabilities: 0.250 0.625 0.000 0.125 0.000 
## 
## Node number 23598: 63 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.00315
##     class counts:    45    10     8     0     0
##    probabilities: 0.714 0.159 0.127 0.000 0.000 
## 
## Node number 23599: 56 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.375  P(node) =0.0028
##     class counts:    35    15     3     3     0
##    probabilities: 0.625 0.268 0.054 0.054 0.000 
##   left son=47198 (48 obs) right son=47199 (8 obs)
##   Primary splits:
##       age               < 80.5   to the left,  improve=1.1607140, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.7653061, (0 missing)
##       reimbursement2008 < 1095   to the left,  improve=0.6020408, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.4726553, (0 missing)
##       depression        < 0.5    to the right, improve=0.3311688, (0 missing)
## 
## Node number 24220: 28 observations
##   predicted class=B1  expected loss=0.3214286  P(node) =0.0014
##     class counts:    19     8     1     0     0
##    probabilities: 0.679 0.286 0.036 0.000 0.000 
## 
## Node number 24221: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     3     5     0     0     0
##    probabilities: 0.375 0.625 0.000 0.000 0.000 
## 
## Node number 24222: 65 observations,    complexity param=6.084576e-05
##   predicted class=B1  expected loss=0.3692308  P(node) =0.00325
##     class counts:    41    16     7     0     1
##    probabilities: 0.631 0.246 0.108 0.000 0.015 
##   left son=48444 (58 obs) right son=48445 (7 obs)
##   Primary splits:
##       reimbursement2008 < 1075   to the left,  improve=1.2435770, (0 missing)
##       copd              < 0.5    to the left,  improve=0.9029915, (0 missing)
##       depression        < 0.5    to the right, improve=0.8761474, (0 missing)
##       age               < 55.5   to the left,  improve=0.7910386, (0 missing)
##       kidney            < 0.5    to the right, improve=0.5612040, (0 missing)
## 
## Node number 24223: 14 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.0007
##     class counts:    10     0     4     0     0
##    probabilities: 0.714 0.000 0.286 0.000 0.000 
## 
## Node number 24618: 16 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.0008
##     class counts:    12     2     2     0     0
##    probabilities: 0.750 0.125 0.125 0.000 0.000 
## 
## Node number 24619: 28 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.5  P(node) =0.0014
##     class counts:    14    11     2     0     1
##    probabilities: 0.500 0.393 0.071 0.000 0.036 
##   left son=49238 (20 obs) right son=49239 (8 obs)
##   Primary splits:
##       reimbursement2008 < 1880   to the left,  improve=2.1500000, (0 missing)
##       age               < 50.5   to the right, improve=0.7857143, (0 missing)
## 
## Node number 24674: 29 observations
##   predicted class=B1  expected loss=0.3793103  P(node) =0.00145
##     class counts:    18     9     2     0     0
##    probabilities: 0.621 0.310 0.069 0.000 0.000 
## 
## Node number 24675: 9 observations
##   predicted class=B2  expected loss=0.5555556  P(node) =0.00045
##     class counts:     3     4     2     0     0
##    probabilities: 0.333 0.444 0.222 0.000 0.000 
## 
## Node number 25452: 12 observations
##   predicted class=B1  expected loss=0.4166667  P(node) =0.0006
##     class counts:     7     1     4     0     0
##    probabilities: 0.583 0.083 0.333 0.000 0.000 
## 
## Node number 25453: 24 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.625  P(node) =0.0012
##     class counts:     9     9     4     2     0
##    probabilities: 0.375 0.375 0.167 0.083 0.000 
##   left son=50906 (16 obs) right son=50907 (8 obs)
##   Primary splits:
##       age               < 70     to the left,  improve=0.5416667, (0 missing)
##       reimbursement2008 < 2545   to the right, improve=0.3326331, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.2916667, (0 missing)
##       depression        < 0.5    to the right, improve=0.1666667, (0 missing)
##   Surrogate splits:
##       stroke            < 0.5    to the left,  agree=0.75, adj=0.25, (0 split)
##       reimbursement2008 < 2525   to the right, agree=0.75, adj=0.25, (0 split)
## 
## Node number 26680: 7 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.00035
##     class counts:     5     1     1     0     0
##    probabilities: 0.714 0.143 0.143 0.000 0.000 
## 
## Node number 26681: 27 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.4814815  P(node) =0.00135
##     class counts:    14    13     0     0     0
##    probabilities: 0.519 0.481 0.000 0.000 0.000 
##   left son=53362 (20 obs) right son=53363 (7 obs)
##   Primary splits:
##       age               < 79.5   to the right, improve=1.02433900, (0 missing)
##       reimbursement2008 < 1950   to the left,  improve=1.02433900, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.05291005, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2040   to the left,  agree=0.815, adj=0.286, (0 split)
## 
## Node number 26758: 27 observations
##   predicted class=B1  expected loss=0.2962963  P(node) =0.00135
##     class counts:    19     4     3     0     1
##    probabilities: 0.704 0.148 0.111 0.000 0.037 
## 
## Node number 26759: 68 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5588235  P(node) =0.0034
##     class counts:    30    23     8     7     0
##    probabilities: 0.441 0.338 0.118 0.103 0.000 
##   left son=53518 (29 obs) right son=53519 (39 obs)
##   Primary splits:
##       reimbursement2008 < 2145   to the right, improve=1.4809120, (0 missing)
##       age               < 66.5   to the right, improve=1.4399320, (0 missing)
##       copd              < 0.5    to the left,  improve=0.7962224, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.4079739, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.2968627, (0 missing)
##   Surrogate splits:
##       age    < 72.5   to the right, agree=0.603, adj=0.069, (0 split)
##       cancer < 0.5    to the right, agree=0.588, adj=0.034, (0 split)
## 
## Node number 26816: 45 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5111111  P(node) =0.00225
##     class counts:    20    22     2     1     0
##    probabilities: 0.444 0.489 0.044 0.022 0.000 
##   left son=53632 (33 obs) right son=53633 (12 obs)
##   Primary splits:
##       age               < 66.5   to the right, improve=1.1686870, (0 missing)
##       reimbursement2008 < 1605   to the right, improve=0.5349850, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.2204060, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2016637, (0 missing)
##       kidney            < 0.5    to the right, improve=0.1888889, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1595   to the right, agree=0.778, adj=0.167, (0 split)
## 
## Node number 26817: 10 observations
##   predicted class=B1  expected loss=0.4  P(node) =0.0005
##     class counts:     6     2     0     2     0
##    probabilities: 0.600 0.200 0.000 0.200 0.000 
## 
## Node number 26818: 7 observations
##   predicted class=B2  expected loss=0.1428571  P(node) =0.00035
##     class counts:     1     6     0     0     0
##    probabilities: 0.143 0.857 0.000 0.000 0.000 
## 
## Node number 26819: 26 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.6153846  P(node) =0.0013
##     class counts:     9    10     4     2     1
##    probabilities: 0.346 0.385 0.154 0.077 0.038 
##   left son=53638 (14 obs) right son=53639 (12 obs)
##   Primary splits:
##       reimbursement2008 < 2005   to the right, improve=0.9926740, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.8057692, (0 missing)
##       age               < 67.5   to the right, improve=0.5337995, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.5095571, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3961828, (0 missing)
##   Surrogate splits:
##       diabetes   < 0.5    to the left,  agree=0.692, adj=0.333, (0 split)
##       age        < 66.5   to the right, agree=0.654, adj=0.250, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.577, adj=0.083, (0 split)
##       arthritis  < 0.5    to the left,  agree=0.577, adj=0.083, (0 split)
## 
## Node number 27482: 15 observations
##   predicted class=B1  expected loss=0.4  P(node) =0.00075
##     class counts:     9     5     1     0     0
##    probabilities: 0.600 0.333 0.067 0.000 0.000 
## 
## Node number 27483: 24 observations
##   predicted class=B2  expected loss=0.4166667  P(node) =0.0012
##     class counts:     5    14     5     0     0
##    probabilities: 0.208 0.583 0.208 0.000 0.000 
## 
## Node number 27486: 33 observations
##   predicted class=B2  expected loss=0.3030303  P(node) =0.00165
##     class counts:     4    23     5     1     0
##    probabilities: 0.121 0.697 0.152 0.030 0.000 
## 
## Node number 27487: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     2     2     3     0     0
##    probabilities: 0.286 0.286 0.429 0.000 0.000 
## 
## Node number 27736: 22 observations
##   predicted class=B1  expected loss=0.3636364  P(node) =0.0011
##     class counts:    14     7     1     0     0
##    probabilities: 0.636 0.318 0.045 0.000 0.000 
## 
## Node number 27737: 8 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0004
##     class counts:     2     4     2     0     0
##    probabilities: 0.250 0.500 0.250 0.000 0.000 
## 
## Node number 27750: 20 observations,    complexity param=0.0001014096
##   predicted class=B1  expected loss=0.5  P(node) =0.001
##     class counts:    10     6     2     2     0
##    probabilities: 0.500 0.300 0.100 0.100 0.000 
##   left son=55500 (8 obs) right son=55501 (12 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the right, improve=1.3833330, (0 missing)
##       reimbursement2008 < 3170   to the left,  improve=1.2166670, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5362637, (0 missing)
##       age               < 74.5   to the left,  improve=0.2343434, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1846154, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 3135   to the left,  agree=0.65, adj=0.125, (0 split)
## 
## Node number 27751: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     1     2     3     0     1
##    probabilities: 0.143 0.286 0.429 0.000 0.143 
## 
## Node number 27754: 12 observations
##   predicted class=B2  expected loss=0.4166667  P(node) =0.0006
##     class counts:     4     7     1     0     0
##    probabilities: 0.333 0.583 0.083 0.000 0.000 
## 
## Node number 27755: 14 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0007
##     class counts:     7     3     3     1     0
##    probabilities: 0.500 0.214 0.214 0.071 0.000 
## 
## Node number 27924: 9 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.00045
##     class counts:     6     2     0     1     0
##    probabilities: 0.667 0.222 0.000 0.111 0.000 
## 
## Node number 27925: 14 observations
##   predicted class=B2  expected loss=0.3571429  P(node) =0.0007
##     class counts:     4     9     1     0     0
##    probabilities: 0.286 0.643 0.071 0.000 0.000 
## 
## Node number 27926: 12 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0006
##     class counts:     8     1     1     2     0
##    probabilities: 0.667 0.083 0.083 0.167 0.000 
## 
## Node number 27927: 9 observations
##   predicted class=B2  expected loss=0.5555556  P(node) =0.00045
##     class counts:     3     4     1     1     0
##    probabilities: 0.333 0.444 0.111 0.111 0.000 
## 
## Node number 28778: 22 observations
##   predicted class=B1  expected loss=0.2727273  P(node) =0.0011
##     class counts:    16     2     4     0     0
##    probabilities: 0.727 0.091 0.182 0.000 0.000 
## 
## Node number 28779: 25 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.52  P(node) =0.00125
##     class counts:    12     4     9     0     0
##    probabilities: 0.480 0.160 0.360 0.000 0.000 
##   left son=57558 (18 obs) right son=57559 (7 obs)
##   Primary splits:
##       reimbursement2008 < 5500   to the left,  improve=1.6933330, (0 missing)
##       age               < 66.5   to the left,  improve=0.3984615, (0 missing)
##       copd              < 0.5    to the left,  improve=0.1516667, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.1238889, (0 missing)
##   Surrogate splits:
##       age < 69.5   to the left,  agree=0.76, adj=0.143, (0 split)
## 
## Node number 30746: 17 observations
##   predicted class=B1  expected loss=0.3529412  P(node) =0.00085
##     class counts:    11     4     2     0     0
##    probabilities: 0.647 0.235 0.118 0.000 0.000 
## 
## Node number 30747: 39 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.6410256  P(node) =0.00195
##     class counts:    14    10    14     1     0
##    probabilities: 0.359 0.256 0.359 0.026 0.000 
##   left son=61494 (16 obs) right son=61495 (23 obs)
##   Primary splits:
##       reimbursement2008 < 4475   to the right, improve=1.2231050, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.7420912, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.5071225, (0 missing)
##       age               < 66.5   to the right, improve=0.4089744, (0 missing)
##       depression        < 0.5    to the left,  improve=0.1756410, (0 missing)
##   Surrogate splits:
##       age < 64     to the right, agree=0.718, adj=0.312, (0 split)
## 
## Node number 30852: 76 observations,    complexity param=0.0003295812
##   predicted class=B1  expected loss=0.4210526  P(node) =0.0038
##     class counts:    44    24     8     0     0
##    probabilities: 0.579 0.316 0.105 0.000 0.000 
##   left son=61704 (48 obs) right son=61705 (28 obs)
##   Primary splits:
##       reimbursement2008 < 8850   to the right, improve=1.9802630, (0 missing)
##       age               < 82.5   to the left,  improve=1.1771250, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.6370279, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3385965, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.2719298, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.961, adj=0.893, (0 split)
##       age        < 74.5   to the right, agree=0.645, adj=0.036, (0 split)
##       ihd        < 0.5    to the right, agree=0.645, adj=0.036, (0 split)
## 
## Node number 30853: 9 observations
##   predicted class=B2  expected loss=0.5555556  P(node) =0.00045
##     class counts:     2     4     2     1     0
##    probabilities: 0.222 0.444 0.222 0.111 0.000 
## 
## Node number 30854: 13 observations
##   predicted class=B1  expected loss=0.5384615  P(node) =0.00065
##     class counts:     6     4     1     2     0
##    probabilities: 0.462 0.308 0.077 0.154 0.000 
## 
## Node number 30855: 8 observations
##   predicted class=B4  expected loss=0.5  P(node) =0.0004
##     class counts:     1     3     0     4     0
##    probabilities: 0.125 0.375 0.000 0.500 0.000 
## 
## Node number 30902: 10 observations
##   predicted class=B2  expected loss=0.3  P(node) =0.0005
##     class counts:     2     7     0     1     0
##    probabilities: 0.200 0.700 0.000 0.100 0.000 
## 
## Node number 30903: 11 observations
##   predicted class=B3  expected loss=0.5454545  P(node) =0.00055
##     class counts:     2     3     5     1     0
##    probabilities: 0.182 0.273 0.455 0.091 0.000 
## 
## Node number 30904: 26 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5  P(node) =0.0013
##     class counts:    13     7     3     3     0
##    probabilities: 0.500 0.269 0.115 0.115 0.000 
##   left son=61808 (18 obs) right son=61809 (8 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=1.7841880, (0 missing)
##       copd              < 0.5    to the left,  improve=1.6382280, (0 missing)
##       reimbursement2008 < 11300  to the left,  improve=0.6975130, (0 missing)
##       age               < 77.5   to the right, improve=0.5230769, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=0.2302665, (0 missing)
##   Surrogate splits:
##       age < 74.5   to the right, agree=0.769, adj=0.25, (0 split)
## 
## Node number 30905: 12 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0006
##     class counts:     2     6     2     2     0
##    probabilities: 0.167 0.500 0.167 0.167 0.000 
## 
## Node number 31524: 8 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.0004
##     class counts:     6     2     0     0     0
##    probabilities: 0.750 0.250 0.000 0.000 0.000 
## 
## Node number 31525: 24 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0012
##     class counts:     6    12     3     2     1
##    probabilities: 0.250 0.500 0.125 0.083 0.042 
## 
## Node number 31656: 10 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0005
##     class counts:     5     2     1     1     1
##    probabilities: 0.500 0.200 0.100 0.100 0.100 
## 
## Node number 31657: 43 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4651163  P(node) =0.00215
##     class counts:     9    23     6     5     0
##    probabilities: 0.209 0.535 0.140 0.116 0.000 
##   left son=63314 (36 obs) right son=63315 (7 obs)
##   Primary splits:
##       reimbursement2008 < 4140   to the right, improve=1.3715390, (0 missing)
##       age               < 78.5   to the right, improve=0.7748360, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.3783034, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.0576865, (0 missing)
## 
## Node number 31658: 15 observations
##   predicted class=B2  expected loss=0.2666667  P(node) =0.00075
##     class counts:     0    11     3     1     0
##    probabilities: 0.000 0.733 0.200 0.067 0.000 
## 
## Node number 31659: 22 observations
##   predicted class=B3  expected loss=0.5454545  P(node) =0.0011
##     class counts:     4     7    10     1     0
##    probabilities: 0.182 0.318 0.455 0.045 0.000 
## 
## Node number 31660: 10 observations
##   predicted class=B2  expected loss=0.3  P(node) =0.0005
##     class counts:     1     7     2     0     0
##    probabilities: 0.100 0.700 0.200 0.000 0.000 
## 
## Node number 31661: 36 observations,    complexity param=0.0002281716
##   predicted class=B3  expected loss=0.5555556  P(node) =0.0018
##     class counts:     6    12    16     2     0
##    probabilities: 0.167 0.333 0.444 0.056 0.000 
##   left son=63322 (21 obs) right son=63323 (15 obs)
##   Primary splits:
##       reimbursement2008 < 8035   to the right, improve=3.2825400, (0 missing)
##       bucket2008        < 2.5    to the right, improve=3.2825400, (0 missing)
##       cancer            < 0.5    to the right, improve=0.7777778, (0 missing)
##       age               < 68.5   to the left,  improve=0.5569986, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4777778, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=1.000, adj=1.000, (0 split)
##       age        < 69.5   to the left,  agree=0.611, adj=0.067, (0 split)
## 
## Node number 31662: 9 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.00045
##     class counts:     6     0     1     1     1
##    probabilities: 0.667 0.000 0.111 0.111 0.111 
## 
## Node number 31663: 19 observations
##   predicted class=B3  expected loss=0.6315789  P(node) =0.00095
##     class counts:     3     6     7     3     0
##    probabilities: 0.158 0.316 0.368 0.158 0.000 
## 
## Node number 31792: 10 observations
##   predicted class=B1  expected loss=0.3  P(node) =0.0005
##     class counts:     7     0     1     1     1
##    probabilities: 0.700 0.000 0.100 0.100 0.100 
## 
## Node number 31793: 14 observations
##   predicted class=B2  expected loss=0.5714286  P(node) =0.0007
##     class counts:     4     6     0     4     0
##    probabilities: 0.286 0.429 0.000 0.286 0.000 
## 
## Node number 31794: 18 observations
##   predicted class=B2  expected loss=0.3888889  P(node) =0.0009
##     class counts:     2    11     4     1     0
##    probabilities: 0.111 0.611 0.222 0.056 0.000 
## 
## Node number 31795: 127 observations,    complexity param=0.0002738059
##   predicted class=B2  expected loss=0.5905512  P(node) =0.00635
##     class counts:    30    52    16    25     4
##    probabilities: 0.236 0.409 0.126 0.197 0.031 
##   left son=63590 (65 obs) right son=63591 (62 obs)
##   Primary splits:
##       age               < 68.5   to the right, improve=1.8156310, (0 missing)
##       reimbursement2008 < 10940  to the left,  improve=1.2503720, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.8431131, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7185236, (0 missing)
##       depression        < 0.5    to the right, improve=0.7180088, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 9780   to the left,  agree=0.551, adj=0.081, (0 split)
##       depression        < 0.5    to the left,  agree=0.543, adj=0.065, (0 split)
##       cancer            < 0.5    to the left,  agree=0.535, adj=0.048, (0 split)
##       copd              < 0.5    to the left,  agree=0.528, adj=0.032, (0 split)
## 
## Node number 31802: 17 observations
##   predicted class=B1  expected loss=0.5882353  P(node) =0.00085
##     class counts:     7     2     5     2     1
##    probabilities: 0.412 0.118 0.294 0.118 0.059 
## 
## Node number 31803: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     0     1     4     2     0
##    probabilities: 0.000 0.143 0.571 0.286 0.000 
## 
## Node number 31804: 23 observations,    complexity param=7.60572e-05
##   predicted class=B2  expected loss=0.4347826  P(node) =0.00115
##     class counts:     2    13     8     0     0
##    probabilities: 0.087 0.565 0.348 0.000 0.000 
##   left son=63608 (13 obs) right son=63609 (10 obs)
##   Primary splits:
##       reimbursement2008 < 11420  to the left,  improve=0.8956522, (0 missing)
##       copd              < 0.5    to the right, improve=0.8320158, (0 missing)
##       age               < 81.5   to the left,  improve=0.7110368, (0 missing)
##       depression        < 0.5    to the left,  improve=0.3940649, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2033445, (0 missing)
##   Surrogate splits:
##       age    < 80.5   to the left,  agree=0.783, adj=0.5, (0 split)
##       stroke < 0.5    to the left,  agree=0.609, adj=0.1, (0 split)
## 
## Node number 31805: 15 observations
##   predicted class=B2  expected loss=0.5333333  P(node) =0.00075
##     class counts:     1     7     2     5     0
##    probabilities: 0.067 0.467 0.133 0.333 0.000 
## 
## Node number 31840: 12 observations
##   predicted class=B1  expected loss=0.4166667  P(node) =0.0006
##     class counts:     7     2     1     2     0
##    probabilities: 0.583 0.167 0.083 0.167 0.000 
## 
## Node number 31841: 13 observations
##   predicted class=B2  expected loss=0.3846154  P(node) =0.00065
##     class counts:     1     8     2     1     1
##    probabilities: 0.077 0.615 0.154 0.077 0.077 
## 
## Node number 31844: 47 observations,    complexity param=0.0003650745
##   predicted class=B1  expected loss=0.6808511  P(node) =0.00235
##     class counts:    15    14    10     6     2
##    probabilities: 0.319 0.298 0.213 0.128 0.043 
##   left son=63688 (7 obs) right son=63689 (40 obs)
##   Primary splits:
##       age               < 60.5   to the left,  improve=1.8709730, (0 missing)
##       reimbursement2008 < 4015   to the right, improve=1.6709730, (0 missing)
##       depression        < 0.5    to the right, improve=0.9065717, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6749409, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.3897557, (0 missing)
## 
## Node number 31845: 47 observations
##   predicted class=B2  expected loss=0.4468085  P(node) =0.00235
##     class counts:     7    26     7     7     0
##    probabilities: 0.149 0.553 0.149 0.149 0.000 
## 
## Node number 31846: 39 observations,    complexity param=0.0003650745
##   predicted class=B2  expected loss=0.6923077  P(node) =0.00195
##     class counts:    11    12     9     6     1
##    probabilities: 0.282 0.308 0.231 0.154 0.026 
##   left son=63692 (15 obs) right son=63693 (24 obs)
##   Primary splits:
##       age               < 76.5   to the right, improve=1.3128210, (0 missing)
##       depression        < 0.5    to the right, improve=1.0842490, (0 missing)
##       reimbursement2008 < 5315   to the left,  improve=0.9900135, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5262614, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.1901824, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 5155   to the left,  agree=0.718, adj=0.267, (0 split)
##       stroke            < 0.5    to the right, agree=0.667, adj=0.133, (0 split)
##       ihd               < 0.5    to the left,  agree=0.641, adj=0.067, (0 split)
## 
## Node number 31847: 29 observations
##   predicted class=B3  expected loss=0.5172414  P(node) =0.00145
##     class counts:     2     6    14     6     1
##    probabilities: 0.069 0.207 0.483 0.207 0.034 
## 
## Node number 32072: 7 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.00035
##     class counts:     4     2     1     0     0
##    probabilities: 0.571 0.286 0.143 0.000 0.000 
## 
## Node number 32073: 15 observations
##   predicted class=B2  expected loss=0.3333333  P(node) =0.00075
##     class counts:     5    10     0     0     0
##    probabilities: 0.333 0.667 0.000 0.000 0.000 
## 
## Node number 32212: 52 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4615385  P(node) =0.0026
##     class counts:     8    28    10     5     1
##    probabilities: 0.154 0.538 0.192 0.096 0.019 
##   left son=64424 (14 obs) right son=64425 (38 obs)
##   Primary splits:
##       reimbursement2008 < 11260  to the left,  improve=2.5399070, (0 missing)
##       alzheimers        < 0.5    to the right, improve=2.0053420, (0 missing)
##       depression        < 0.5    to the right, improve=0.6965171, (0 missing)
##       age               < 75.5   to the left,  improve=0.5668498, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5579070, (0 missing)
##   Surrogate splits:
##       age < 57     to the left,  agree=0.75, adj=0.071, (0 split)
## 
## Node number 32213: 78 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.525641  P(node) =0.0039
##     class counts:     5    37    26     9     1
##    probabilities: 0.064 0.474 0.333 0.115 0.013 
##   left son=64426 (37 obs) right son=64427 (41 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=0.6238358, (0 missing)
##       age               < 79.5   to the left,  improve=0.6101157, (0 missing)
##       reimbursement2008 < 10045  to the right, improve=0.6069777, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3743760, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.3659016, (0 missing)
##   Surrogate splits:
##       age               < 76     to the left,  agree=0.628, adj=0.216, (0 split)
##       reimbursement2008 < 9585   to the right, agree=0.590, adj=0.135, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.564, adj=0.081, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.551, adj=0.054, (0 split)
##       copd              < 0.5    to the left,  agree=0.538, adj=0.027, (0 split)
## 
## Node number 32214: 14 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0007
##     class counts:     0     7     5     0     2
##    probabilities: 0.000 0.500 0.357 0.000 0.143 
## 
## Node number 32215: 8 observations
##   predicted class=B3  expected loss=0.375  P(node) =0.0004
##     class counts:     0     1     5     2     0
##    probabilities: 0.000 0.125 0.625 0.250 0.000 
## 
## Node number 32516: 23 observations
##   predicted class=B1  expected loss=0.4782609  P(node) =0.00115
##     class counts:    12     2     3     6     0
##    probabilities: 0.522 0.087 0.130 0.261 0.000 
## 
## Node number 32517: 18 observations
##   predicted class=B3  expected loss=0.6666667  P(node) =0.0009
##     class counts:     3     5     6     4     0
##    probabilities: 0.167 0.278 0.333 0.222 0.000 
## 
## Node number 32564: 10 observations
##   predicted class=B3  expected loss=0.5  P(node) =0.0005
##     class counts:     2     3     5     0     0
##    probabilities: 0.200 0.300 0.500 0.000 0.000 
## 
## Node number 32565: 29 observations,    complexity param=0.000380286
##   predicted class=B4  expected loss=0.6896552  P(node) =0.00145
##     class counts:     7     8     4     9     1
##    probabilities: 0.241 0.276 0.138 0.310 0.034 
##   left son=65130 (22 obs) right son=65131 (7 obs)
##   Primary splits:
##       age               < 83.5   to the right, improve=1.5293330, (0 missing)
##       reimbursement2008 < 17795  to the right, improve=1.3395230, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5796935, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5726228, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.4006085, (0 missing)
## 
## Node number 32584: 10 observations
##   predicted class=B2  expected loss=0.6  P(node) =0.0005
##     class counts:     3     4     3     0     0
##    probabilities: 0.300 0.400 0.300 0.000 0.000 
## 
## Node number 32585: 10 observations
##   predicted class=B1  expected loss=0.4  P(node) =0.0005
##     class counts:     6     0     1     3     0
##    probabilities: 0.600 0.000 0.100 0.300 0.000 
## 
## Node number 32590: 10 observations
##   predicted class=B3  expected loss=0.5  P(node) =0.0005
##     class counts:     0     3     5     1     1
##    probabilities: 0.000 0.300 0.500 0.100 0.100 
## 
## Node number 32591: 15 observations
##   predicted class=B4  expected loss=0.6  P(node) =0.00075
##     class counts:     0     5     3     6     1
##    probabilities: 0.000 0.333 0.200 0.400 0.067 
## 
## Node number 32748: 26 observations
##   predicted class=B2  expected loss=0.4615385  P(node) =0.0013
##     class counts:     0    14     3     9     0
##    probabilities: 0.000 0.538 0.115 0.346 0.000 
## 
## Node number 32749: 13 observations
##   predicted class=B4  expected loss=0.3846154  P(node) =0.00065
##     class counts:     0     5     0     8     0
##    probabilities: 0.000 0.385 0.000 0.615 0.000 
## 
## Node number 32752: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     0     5     0     2     0
##    probabilities: 0.000 0.714 0.000 0.286 0.000 
## 
## Node number 32753: 132 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6742424  P(node) =0.0066
##     class counts:    14    43    36    34     5
##    probabilities: 0.106 0.326 0.273 0.258 0.038 
##   left son=65506 (72 obs) right son=65507 (60 obs)
##   Primary splits:
##       age               < 68.5   to the right, improve=1.3924240, (0 missing)
##       reimbursement2008 < 55300  to the right, improve=1.1164590, (0 missing)
##       bucket2008        < 4.5    to the right, improve=1.1164590, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9824242, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.9510963, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 65275  to the left,  agree=0.621, adj=0.167, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.561, adj=0.033, (0 split)
## 
## Node number 32758: 10 observations
##   predicted class=B3  expected loss=0.5  P(node) =0.0005
##     class counts:     0     1     5     4     0
##    probabilities: 0.000 0.100 0.500 0.400 0.000 
## 
## Node number 32759: 11 observations
##   predicted class=B4  expected loss=0.3636364  P(node) =0.00055
##     class counts:     0     2     2     7     0
##    probabilities: 0.000 0.182 0.182 0.636 0.000 
## 
## Node number 32760: 19 observations
##   predicted class=B3  expected loss=0.6315789  P(node) =0.00095
##     class counts:     2     6     7     4     0
##    probabilities: 0.105 0.316 0.368 0.211 0.000 
## 
## Node number 32761: 8 observations
##   predicted class=B4  expected loss=0.5  P(node) =0.0004
##     class counts:     0     2     1     4     1
##    probabilities: 0.000 0.250 0.125 0.500 0.125 
## 
## Node number 47198: 48 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0024
##     class counts:    32    11     3     2     0
##    probabilities: 0.667 0.229 0.062 0.042 0.000 
##   left son=94396 (38 obs) right son=94397 (10 obs)
##   Primary splits:
##       age               < 74.5   to the left,  improve=0.9486842, (0 missing)
##       reimbursement2008 < 975    to the right, improve=0.4675926, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2881868, (0 missing)
##       depression        < 0.5    to the right, improve=0.1600123, (0 missing)
## 
## Node number 47199: 8 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0004
##     class counts:     3     4     0     1     0
##    probabilities: 0.375 0.500 0.000 0.125 0.000 
## 
## Node number 48444: 58 observations
##   predicted class=B1  expected loss=0.3448276  P(node) =0.0029
##     class counts:    38    12     7     0     1
##    probabilities: 0.655 0.207 0.121 0.000 0.017 
## 
## Node number 48445: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     3     4     0     0     0
##    probabilities: 0.429 0.571 0.000 0.000 0.000 
## 
## Node number 49238: 20 observations
##   predicted class=B1  expected loss=0.35  P(node) =0.001
##     class counts:    13     7     0     0     0
##    probabilities: 0.650 0.350 0.000 0.000 0.000 
## 
## Node number 49239: 8 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0004
##     class counts:     1     4     2     0     1
##    probabilities: 0.125 0.500 0.250 0.000 0.125 
## 
## Node number 50906: 16 observations
##   predicted class=B2  expected loss=0.5625  P(node) =0.0008
##     class counts:     6     7     3     0     0
##    probabilities: 0.375 0.438 0.188 0.000 0.000 
## 
## Node number 50907: 8 observations
##   predicted class=B1  expected loss=0.625  P(node) =0.0004
##     class counts:     3     2     1     2     0
##    probabilities: 0.375 0.250 0.125 0.250 0.000 
## 
## Node number 53362: 20 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.4  P(node) =0.001
##     class counts:    12     8     0     0     0
##    probabilities: 0.600 0.400 0.000 0.000 0.000 
##   left son=106724 (9 obs) right son=106725 (11 obs)
##   Primary splits:
##       reimbursement2008 < 1790   to the left,  improve=1.0343430, (0 missing)
##       age               < 83.5   to the left,  improve=0.2813187, (0 missing)
##   Surrogate splits:
##       alzheimers < 0.5    to the right, agree=0.65, adj=0.222, (0 split)
##       age        < 81.5   to the right, agree=0.60, adj=0.111, (0 split)
## 
## Node number 53363: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     2     5     0     0     0
##    probabilities: 0.286 0.714 0.000 0.000 0.000 
## 
## Node number 53518: 29 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4482759  P(node) =0.00145
##     class counts:    16     7     5     1     0
##    probabilities: 0.552 0.241 0.172 0.034 0.000 
##   left son=107036 (17 obs) right son=107037 (12 obs)
##   Primary splits:
##       age               < 69.5   to the right, improve=1.65483400, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.09270000, (0 missing)
##       reimbursement2008 < 2385   to the left,  improve=0.89789520, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.59811170, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.04075235, (0 missing)
##   Surrogate splits:
##       arthritis         < 0.5    to the left,  agree=0.690, adj=0.250, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.655, adj=0.167, (0 split)
##       reimbursement2008 < 2405   to the left,  agree=0.655, adj=0.167, (0 split)
## 
## Node number 53519: 39 observations,    complexity param=0.0002028192
##   predicted class=B2  expected loss=0.5897436  P(node) =0.00195
##     class counts:    14    16     3     6     0
##    probabilities: 0.359 0.410 0.077 0.154 0.000 
##   left son=107038 (30 obs) right son=107039 (9 obs)
##   Primary splits:
##       reimbursement2008 < 2065   to the left,  improve=1.03418800, (0 missing)
##       age               < 67.5   to the right, improve=0.29641030, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.26290380, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.14529910, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.07020336, (0 missing)
##   Surrogate splits:
##       age < 64.5   to the right, agree=0.795, adj=0.111, (0 split)
## 
## Node number 53632: 33 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.4848485  P(node) =0.00165
##     class counts:    17    14     1     1     0
##    probabilities: 0.515 0.424 0.030 0.030 0.000 
##   left son=107264 (18 obs) right son=107265 (15 obs)
##   Primary splits:
##       reimbursement2008 < 1715   to the left,  improve=0.7535354, (0 missing)
##       age               < 70.5   to the left,  improve=0.5151515, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1724242, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.1471861, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.0479798, (0 missing)
##   Surrogate splits:
##       age      < 70.5   to the left,  agree=0.697, adj=0.333, (0 split)
##       diabetes < 0.5    to the left,  agree=0.636, adj=0.200, (0 split)
##       kidney   < 0.5    to the right, agree=0.576, adj=0.067, (0 split)
## 
## Node number 53633: 12 observations
##   predicted class=B2  expected loss=0.3333333  P(node) =0.0006
##     class counts:     3     8     1     0     0
##    probabilities: 0.250 0.667 0.083 0.000 0.000 
## 
## Node number 53638: 14 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0007
##     class counts:     7     5     1     1     0
##    probabilities: 0.500 0.357 0.071 0.071 0.000 
## 
## Node number 53639: 12 observations
##   predicted class=B2  expected loss=0.5833333  P(node) =0.0006
##     class counts:     2     5     3     1     1
##    probabilities: 0.167 0.417 0.250 0.083 0.083 
## 
## Node number 55500: 8 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.0004
##     class counts:     6     1     0     1     0
##    probabilities: 0.750 0.125 0.000 0.125 0.000 
## 
## Node number 55501: 12 observations
##   predicted class=B2  expected loss=0.5833333  P(node) =0.0006
##     class counts:     4     5     2     1     0
##    probabilities: 0.333 0.417 0.167 0.083 0.000 
## 
## Node number 57558: 18 observations
##   predicted class=B1  expected loss=0.3888889  P(node) =0.0009
##     class counts:    11     2     5     0     0
##    probabilities: 0.611 0.111 0.278 0.000 0.000 
## 
## Node number 57559: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     1     2     4     0     0
##    probabilities: 0.143 0.286 0.571 0.000 0.000 
## 
## Node number 61494: 16 observations
##   predicted class=B1  expected loss=0.625  P(node) =0.0008
##     class counts:     6     6     3     1     0
##    probabilities: 0.375 0.375 0.188 0.062 0.000 
## 
## Node number 61495: 23 observations,    complexity param=0.0001521144
##   predicted class=B3  expected loss=0.5217391  P(node) =0.00115
##     class counts:     8     4    11     0     0
##    probabilities: 0.348 0.174 0.478 0.000 0.000 
##   left son=122990 (10 obs) right son=122991 (13 obs)
##   Primary splits:
##       age               < 59     to the left,  improve=0.98394650, (0 missing)
##       reimbursement2008 < 4195   to the right, improve=0.83229810, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.64420290, (0 missing)
##       depression        < 0.5    to the right, improve=0.05452036, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.04420290, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4100   to the right, agree=0.652, adj=0.2, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.609, adj=0.1, (0 split)
## 
## Node number 61704: 48 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0024
##     class counts:    32    11     5     0     0
##    probabilities: 0.667 0.229 0.104 0.000 0.000 
## 
## Node number 61705: 28 observations,    complexity param=0.0003295812
##   predicted class=B2  expected loss=0.5357143  P(node) =0.0014
##     class counts:    12    13     3     0     0
##    probabilities: 0.429 0.464 0.107 0.000 0.000 
##   left son=123410 (13 obs) right son=123411 (15 obs)
##   Primary splits:
##       reimbursement2008 < 6985   to the left,  improve=4.0794870, (0 missing)
##       copd              < 0.5    to the left,  improve=0.9812834, (0 missing)
##       age               < 80.5   to the left,  improve=0.5000000, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4692308, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.3750000, (0 missing)
##   Surrogate splits:
##       heart.failure < 0.5    to the left,  agree=0.643, adj=0.231, (0 split)
##       age           < 83     to the right, agree=0.571, adj=0.077, (0 split)
##       bucket2008    < 2.5    to the left,  agree=0.571, adj=0.077, (0 split)
## 
## Node number 61808: 18 observations
##   predicted class=B1  expected loss=0.3888889  P(node) =0.0009
##     class counts:    11     4     0     3     0
##    probabilities: 0.611 0.222 0.000 0.167 0.000 
## 
## Node number 61809: 8 observations
##   predicted class=B2  expected loss=0.625  P(node) =0.0004
##     class counts:     2     3     3     0     0
##    probabilities: 0.250 0.375 0.375 0.000 0.000 
## 
## Node number 63314: 36 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4166667  P(node) =0.0018
##     class counts:     8    21     5     2     0
##    probabilities: 0.222 0.583 0.139 0.056 0.000 
##   left son=126628 (13 obs) right son=126629 (23 obs)
##   Primary splits:
##       reimbursement2008 < 5440   to the left,  improve=1.9760310, (0 missing)
##       age               < 74.5   to the left,  improve=0.7500000, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.5921212, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.1449948, (0 missing)
##   Surrogate splits:
##       age        < 81.5   to the right, agree=0.667, adj=0.077, (0 split)
##       cancer     < 0.5    to the right, agree=0.667, adj=0.077, (0 split)
##       stroke     < 0.5    to the right, agree=0.667, adj=0.077, (0 split)
##       bucket2008 < 2.5    to the left,  agree=0.667, adj=0.077, (0 split)
## 
## Node number 63315: 7 observations
##   predicted class=B4  expected loss=0.5714286  P(node) =0.00035
##     class counts:     1     2     1     3     0
##    probabilities: 0.143 0.286 0.143 0.429 0.000 
## 
## Node number 63322: 21 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5238095  P(node) =0.00105
##     class counts:     4    10     5     2     0
##    probabilities: 0.190 0.476 0.238 0.095 0.000 
##   left son=126644 (9 obs) right son=126645 (12 obs)
##   Primary splits:
##       age               < 67.5   to the left,  improve=1.4841270, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8174603, (0 missing)
##       reimbursement2008 < 11715  to the left,  improve=0.6529304, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4406926, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.2619048, (0 missing)
##   Surrogate splits:
##       cancer            < 0.5    to the right, agree=0.714, adj=0.333, (0 split)
##       reimbursement2008 < 10315  to the left,  agree=0.714, adj=0.333, (0 split)
##       osteoporosis      < 0.5    to the right, agree=0.619, adj=0.111, (0 split)
## 
## Node number 63323: 15 observations
##   predicted class=B3  expected loss=0.2666667  P(node) =0.00075
##     class counts:     2     2    11     0     0
##    probabilities: 0.133 0.133 0.733 0.000 0.000 
## 
## Node number 63590: 65 observations,    complexity param=0.0002738059
##   predicted class=B2  expected loss=0.5230769  P(node) =0.00325
##     class counts:    16    31    10     7     1
##    probabilities: 0.246 0.477 0.154 0.108 0.015 
##   left son=127180 (39 obs) right son=127181 (26 obs)
##   Primary splits:
##       reimbursement2008 < 10335  to the left,  improve=2.6871790, (0 missing)
##       age               < 71.5   to the left,  improve=1.7206540, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.6230770, (0 missing)
##       ihd               < 0.5    to the right, improve=1.3879500, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.8410256, (0 missing)
##   Surrogate splits:
##       alzheimers < 0.5    to the left,  agree=0.631, adj=0.077, (0 split)
##       copd       < 0.5    to the left,  agree=0.631, adj=0.077, (0 split)
##       bucket2008 < 2.5    to the left,  agree=0.631, adj=0.077, (0 split)
##       cancer     < 0.5    to the left,  agree=0.615, adj=0.038, (0 split)
## 
## Node number 63591: 62 observations,    complexity param=0.0002738059
##   predicted class=B2  expected loss=0.6612903  P(node) =0.0031
##     class counts:    14    21     6    18     3
##    probabilities: 0.226 0.339 0.097 0.290 0.048 
##   left son=127182 (28 obs) right son=127183 (34 obs)
##   Primary splits:
##       reimbursement2008 < 10290  to the right, improve=1.5262940, (0 missing)
##       age               < 52     to the left,  improve=1.5139440, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.4593000, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9970196, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5110357, (0 missing)
##   Surrogate splits:
##       bucket2008    < 2.5    to the right, agree=0.694, adj=0.321, (0 split)
##       cancer        < 0.5    to the right, agree=0.613, adj=0.143, (0 split)
##       heart.failure < 0.5    to the right, agree=0.597, adj=0.107, (0 split)
##       age           < 64.5   to the right, agree=0.581, adj=0.071, (0 split)
##       copd          < 0.5    to the right, agree=0.581, adj=0.071, (0 split)
## 
## Node number 63608: 13 observations
##   predicted class=B2  expected loss=0.3076923  P(node) =0.00065
##     class counts:     1     9     3     0     0
##    probabilities: 0.077 0.692 0.231 0.000 0.000 
## 
## Node number 63609: 10 observations
##   predicted class=B3  expected loss=0.5  P(node) =0.0005
##     class counts:     1     4     5     0     0
##    probabilities: 0.100 0.400 0.500 0.000 0.000 
## 
## Node number 63688: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     1     5     1     0     0
##    probabilities: 0.143 0.714 0.143 0.000 0.000 
## 
## Node number 63689: 40 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.65  P(node) =0.002
##     class counts:    14     9     9     6     2
##    probabilities: 0.350 0.225 0.225 0.150 0.050 
##   left son=127378 (14 obs) right son=127379 (26 obs)
##   Primary splits:
##       age               < 71.5   to the left,  improve=1.6214290, (0 missing)
##       reimbursement2008 < 3615   to the right, improve=1.0129630, (0 missing)
##       depression        < 0.5    to the right, improve=0.7313187, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5512788, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.3700000, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4015   to the right, agree=0.700, adj=0.143, (0 split)
##       osteoporosis      < 0.5    to the right, agree=0.675, adj=0.071, (0 split)
## 
## Node number 63692: 15 observations
##   predicted class=B3  expected loss=0.6  P(node) =0.00075
##     class counts:     4     5     6     0     0
##    probabilities: 0.267 0.333 0.400 0.000 0.000 
## 
## Node number 63693: 24 observations,    complexity param=0.0003650745
##   predicted class=B1  expected loss=0.7083333  P(node) =0.0012
##     class counts:     7     7     3     6     1
##    probabilities: 0.292 0.292 0.125 0.250 0.042 
##   left son=127386 (14 obs) right son=127387 (10 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=1.9714290, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8333333, (0 missing)
##       reimbursement2008 < 5315   to the left,  improve=0.7555556, (0 missing)
##       age               < 67.5   to the right, improve=0.6250000, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5594406, (0 missing)
##   Surrogate splits:
##       age               < 75.5   to the left,  agree=0.708, adj=0.3, (0 split)
##       cancer            < 0.5    to the left,  agree=0.708, adj=0.3, (0 split)
##       reimbursement2008 < 5035   to the right, agree=0.667, adj=0.2, (0 split)
##       copd              < 0.5    to the right, agree=0.625, adj=0.1, (0 split)
## 
## Node number 64424: 14 observations
##   predicted class=B2  expected loss=0.1428571  P(node) =0.0007
##     class counts:     1    12     1     0     0
##    probabilities: 0.071 0.857 0.071 0.000 0.000 
## 
## Node number 64425: 38 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5789474  P(node) =0.0019
##     class counts:     7    16     9     5     1
##    probabilities: 0.184 0.421 0.237 0.132 0.026 
##   left son=128850 (25 obs) right son=128851 (13 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the right, improve=1.7548180, (0 missing)
##       reimbursement2008 < 12915  to the right, improve=1.5553310, (0 missing)
##       copd              < 0.5    to the left,  improve=0.7455870, (0 missing)
##       depression        < 0.5    to the right, improve=0.6704998, (0 missing)
##       age               < 85     to the right, improve=0.5436090, (0 missing)
## 
## Node number 64426: 37 observations
##   predicted class=B2  expected loss=0.4594595  P(node) =0.00185
##     class counts:     3    20    10     4     0
##    probabilities: 0.081 0.541 0.270 0.108 0.000 
## 
## Node number 64427: 41 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5853659  P(node) =0.00205
##     class counts:     2    17    16     5     1
##    probabilities: 0.049 0.415 0.390 0.122 0.024 
##   left son=128854 (34 obs) right son=128855 (7 obs)
##   Primary splits:
##       reimbursement2008 < 10175  to the left,  improve=0.9840131, (0 missing)
##       age               < 64.5   to the left,  improve=0.7571224, (0 missing)
##       stroke            < 0.5    to the right, improve=0.6917388, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.3468219, (0 missing)
##       copd              < 0.5    to the left,  improve=0.2795313, (0 missing)
## 
## Node number 65130: 22 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.6363636  P(node) =0.0011
##     class counts:     6     8     3     5     0
##    probabilities: 0.273 0.364 0.136 0.227 0.000 
##   left son=130260 (10 obs) right son=130261 (12 obs)
##   Primary splits:
##       reimbursement2008 < 17685  to the right, improve=0.7424242, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7305195, (0 missing)
##       age               < 86.5   to the right, improve=0.5415695, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3706294, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.727, adj=0.4, (0 split)
##       age        < 87.5   to the left,  agree=0.591, adj=0.1, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.591, adj=0.1, (0 split)
## 
## Node number 65131: 7 observations
##   predicted class=B4  expected loss=0.4285714  P(node) =0.00035
##     class counts:     1     0     1     4     1
##    probabilities: 0.143 0.000 0.143 0.571 0.143 
## 
## Node number 65506: 72 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6666667  P(node) =0.0036
##     class counts:    11    24    14    20     3
##    probabilities: 0.153 0.333 0.194 0.278 0.042 
##   left son=131012 (65 obs) right son=131013 (7 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the right, improve=1.701282, (0 missing)
##       reimbursement2008 < 55300  to the right, improve=1.679167, (0 missing)
##       bucket2008        < 4.5    to the right, improve=1.679167, (0 missing)
##       age               < 72.5   to the left,  improve=1.502101, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.261148, (0 missing)
## 
## Node number 65507: 60 observations,    complexity param=0.0004563432
##   predicted class=B3  expected loss=0.6333333  P(node) =0.003
##     class counts:     3    19    22    14     2
##    probabilities: 0.050 0.317 0.367 0.233 0.033 
##   left son=131014 (38 obs) right son=131015 (22 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=1.7395530, (0 missing)
##       reimbursement2008 < 44435  to the left,  improve=1.6555560, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.1000000, (0 missing)
##       age               < 59.5   to the right, improve=0.5781297, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4219048, (0 missing)
##   Surrogate splits:
##       age < 66.5   to the left,  agree=0.65, adj=0.045, (0 split)
## 
## Node number 94396: 38 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3684211  P(node) =0.0019
##     class counts:    24    11     2     1     0
##    probabilities: 0.632 0.289 0.053 0.026 0.000 
##   left son=188792 (18 obs) right son=188793 (20 obs)
##   Primary splits:
##       reimbursement2008 < 975    to the right, improve=1.00409400, (0 missing)
##       age               < 71.5   to the left,  improve=0.83583960, (0 missing)
##       depression        < 0.5    to the right, improve=0.22677660, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.07803993, (0 missing)
##   Surrogate splits:
##       age        < 68.5   to the left,  agree=0.658, adj=0.278, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.605, adj=0.167, (0 split)
##       arthritis  < 0.5    to the right, agree=0.553, adj=0.056, (0 split)
##       depression < 0.5    to the right, agree=0.553, adj=0.056, (0 split)
## 
## Node number 94397: 10 observations
##   predicted class=B1  expected loss=0.2  P(node) =0.0005
##     class counts:     8     0     1     1     0
##    probabilities: 0.800 0.000 0.100 0.100 0.000 
## 
## Node number 106724: 9 observations
##   predicted class=B1  expected loss=0.2222222  P(node) =0.00045
##     class counts:     7     2     0     0     0
##    probabilities: 0.778 0.222 0.000 0.000 0.000 
## 
## Node number 106725: 11 observations
##   predicted class=B2  expected loss=0.4545455  P(node) =0.00055
##     class counts:     5     6     0     0     0
##    probabilities: 0.455 0.545 0.000 0.000 0.000 
## 
## Node number 107036: 17 observations
##   predicted class=B1  expected loss=0.2941176  P(node) =0.00085
##     class counts:    12     2     3     0     0
##    probabilities: 0.706 0.118 0.176 0.000 0.000 
## 
## Node number 107037: 12 observations
##   predicted class=B2  expected loss=0.5833333  P(node) =0.0006
##     class counts:     4     5     2     1     0
##    probabilities: 0.333 0.417 0.167 0.083 0.000 
## 
## Node number 107038: 30 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5666667  P(node) =0.0015
##     class counts:    13    11     2     4     0
##    probabilities: 0.433 0.367 0.067 0.133 0.000 
##   left son=214076 (12 obs) right son=214077 (18 obs)
##   Primary splits:
##       reimbursement2008 < 1910   to the right, improve=2.00000000, (0 missing)
##       age               < 71.5   to the left,  improve=0.27777780, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.07660455, (0 missing)
##   Surrogate splits:
##       arthritis < 0.5    to the right, agree=0.733, adj=0.333, (0 split)
##       age       < 72.5   to the right, agree=0.667, adj=0.167, (0 split)
##       copd      < 0.5    to the right, agree=0.633, adj=0.083, (0 split)
## 
## Node number 107039: 9 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.00045
##     class counts:     1     5     1     2     0
##    probabilities: 0.111 0.556 0.111 0.222 0.000 
## 
## Node number 107264: 18 observations
##   predicted class=B1  expected loss=0.3888889  P(node) =0.0009
##     class counts:    11     6     0     1     0
##    probabilities: 0.611 0.333 0.000 0.056 0.000 
## 
## Node number 107265: 15 observations
##   predicted class=B2  expected loss=0.4666667  P(node) =0.00075
##     class counts:     6     8     1     0     0
##    probabilities: 0.400 0.533 0.067 0.000 0.000 
## 
## Node number 122990: 10 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0005
##     class counts:     5     2     3     0     0
##    probabilities: 0.500 0.200 0.300 0.000 0.000 
## 
## Node number 122991: 13 observations
##   predicted class=B3  expected loss=0.3846154  P(node) =0.00065
##     class counts:     3     2     8     0     0
##    probabilities: 0.231 0.154 0.615 0.000 0.000 
## 
## Node number 123410: 13 observations
##   predicted class=B1  expected loss=0.3076923  P(node) =0.00065
##     class counts:     9     2     2     0     0
##    probabilities: 0.692 0.154 0.154 0.000 0.000 
## 
## Node number 123411: 15 observations
##   predicted class=B2  expected loss=0.2666667  P(node) =0.00075
##     class counts:     3    11     1     0     0
##    probabilities: 0.200 0.733 0.067 0.000 0.000 
## 
## Node number 126628: 13 observations
##   predicted class=B2  expected loss=0.1538462  P(node) =0.00065
##     class counts:     1    11     1     0     0
##    probabilities: 0.077 0.846 0.077 0.000 0.000 
## 
## Node number 126629: 23 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5652174  P(node) =0.00115
##     class counts:     7    10     4     2     0
##    probabilities: 0.304 0.435 0.174 0.087 0.000 
##   left son=253258 (7 obs) right son=253259 (16 obs)
##   Primary splits:
##       reimbursement2008 < 5980   to the left,  improve=1.2771740, (0 missing)
##       age               < 74.5   to the left,  improve=0.9688406, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.5309618, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.2279315, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.783, adj=0.286, (0 split)
## 
## Node number 126644: 9 observations
##   predicted class=B1  expected loss=0.6666667  P(node) =0.00045
##     class counts:     3     2     3     1     0
##    probabilities: 0.333 0.222 0.333 0.111 0.000 
## 
## Node number 126645: 12 observations
##   predicted class=B2  expected loss=0.3333333  P(node) =0.0006
##     class counts:     1     8     2     1     0
##    probabilities: 0.083 0.667 0.167 0.083 0.000 
## 
## Node number 127180: 39 observations,    complexity param=0.0002738059
##   predicted class=B1  expected loss=0.6410256  P(node) =0.00195
##     class counts:    14    14     7     4     0
##    probabilities: 0.359 0.359 0.179 0.103 0.000 
##   left son=254360 (8 obs) right son=254361 (31 obs)
##   Primary splits:
##       reimbursement2008 < 9355   to the right, improve=2.2578580, (0 missing)
##       age               < 71.5   to the left,  improve=1.1925780, (0 missing)
##       depression        < 0.5    to the right, improve=1.1320510, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9857550, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8153846, (0 missing)
## 
## Node number 127181: 26 observations
##   predicted class=B2  expected loss=0.3461538  P(node) =0.0013
##     class counts:     2    17     3     3     1
##    probabilities: 0.077 0.654 0.115 0.115 0.038 
## 
## Node number 127182: 28 observations,    complexity param=0.0002738059
##   predicted class=B4  expected loss=0.6428571  P(node) =0.0014
##     class counts:     9     6     2    10     1
##    probabilities: 0.321 0.214 0.071 0.357 0.036 
##   left son=254364 (7 obs) right son=254365 (21 obs)
##   Primary splits:
##       reimbursement2008 < 10940  to the left,  improve=1.880952, (0 missing)
##       age               < 66.5   to the right, improve=1.121429, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.715873, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.515873, (0 missing)
##       depression        < 0.5    to the left,  improve=0.500000, (0 missing)
## 
## Node number 127183: 34 observations,    complexity param=0.0002738059
##   predicted class=B2  expected loss=0.5588235  P(node) =0.0017
##     class counts:     5    15     4     8     2
##    probabilities: 0.147 0.441 0.118 0.235 0.059 
##   left son=254366 (25 obs) right son=254367 (9 obs)
##   Primary splits:
##       age               < 65.5   to the left,  improve=1.9009150, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.7219250, (0 missing)
##       reimbursement2008 < 8370   to the right, improve=1.2050420, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.5834881, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5050420, (0 missing)
## 
## Node number 127378: 14 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.0007
##     class counts:     8     3     1     2     0
##    probabilities: 0.571 0.214 0.071 0.143 0.000 
## 
## Node number 127379: 26 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.6923077  P(node) =0.0013
##     class counts:     6     6     8     4     2
##    probabilities: 0.231 0.231 0.308 0.154 0.077 
##   left son=254758 (19 obs) right son=254759 (7 obs)
##   Primary splits:
##       reimbursement2008 < 3885   to the left,  improve=1.2631580, (0 missing)
##       age               < 75.5   to the right, improve=0.8969697, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6388889, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.4967320, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4444444, (0 missing)
## 
## Node number 127386: 14 observations
##   predicted class=B2  expected loss=0.5714286  P(node) =0.0007
##     class counts:     5     6     1     1     1
##    probabilities: 0.357 0.429 0.071 0.071 0.071 
## 
## Node number 127387: 10 observations
##   predicted class=B4  expected loss=0.5  P(node) =0.0005
##     class counts:     2     1     2     5     0
##    probabilities: 0.200 0.100 0.200 0.500 0.000 
## 
## Node number 128850: 25 observations
##   predicted class=B2  expected loss=0.48  P(node) =0.00125
##     class counts:     5    13     3     3     1
##    probabilities: 0.200 0.520 0.120 0.120 0.040 
## 
## Node number 128851: 13 observations
##   predicted class=B3  expected loss=0.5384615  P(node) =0.00065
##     class counts:     2     3     6     2     0
##    probabilities: 0.154 0.231 0.462 0.154 0.000 
## 
## Node number 128854: 34 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5294118  P(node) =0.0017
##     class counts:     1    16    12     4     1
##    probabilities: 0.029 0.471 0.353 0.118 0.029 
##   left son=257708 (7 obs) right son=257709 (27 obs)
##   Primary splits:
##       reimbursement2008 < 9480   to the right, improve=0.9333956, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7647059, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5044172, (0 missing)
##       stroke            < 0.5    to the right, improve=0.4174208, (0 missing)
##       age               < 77.5   to the left,  improve=0.4003268, (0 missing)
## 
## Node number 128855: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     1     1     4     1     0
##    probabilities: 0.143 0.143 0.571 0.143 0.000 
## 
## Node number 130260: 10 observations
##   predicted class=B1  expected loss=0.6  P(node) =0.0005
##     class counts:     4     3     2     1     0
##    probabilities: 0.400 0.300 0.200 0.100 0.000 
## 
## Node number 130261: 12 observations
##   predicted class=B2  expected loss=0.5833333  P(node) =0.0006
##     class counts:     2     5     1     4     0
##    probabilities: 0.167 0.417 0.083 0.333 0.000 
## 
## Node number 131012: 65 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6307692  P(node) =0.00325
##     class counts:     9    24    13    16     3
##    probabilities: 0.138 0.369 0.200 0.246 0.046 
##   left son=262024 (46 obs) right son=262025 (19 obs)
##   Primary splits:
##       age               < 72.5   to the right, improve=1.560922, (0 missing)
##       reimbursement2008 < 55990  to the right, improve=1.281022, (0 missing)
##       bucket2008        < 4.5    to the right, improve=1.276687, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.268239, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.084950, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 69985  to the left,  agree=0.723, adj=0.053, (0 split)
## 
## Node number 131013: 7 observations
##   predicted class=B4  expected loss=0.4285714  P(node) =0.00035
##     class counts:     2     0     1     4     0
##    probabilities: 0.286 0.000 0.143 0.571 0.000 
## 
## Node number 131014: 38 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.5263158  P(node) =0.0019
##     class counts:     2    10    18     7     1
##    probabilities: 0.053 0.263 0.474 0.184 0.026 
##   left son=262028 (16 obs) right son=262029 (22 obs)
##   Primary splits:
##       reimbursement2008 < 44435  to the left,  improve=1.4210530, (0 missing)
##       depression        < 0.5    to the right, improve=1.1577470, (0 missing)
##       age               < 44     to the left,  improve=0.8219743, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.6702834, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5996241, (0 missing)
##   Surrogate splits:
##       bucket2008 < 4.5    to the left,  agree=0.789, adj=0.500, (0 split)
##       copd       < 0.5    to the left,  agree=0.737, adj=0.375, (0 split)
##       cancer     < 0.5    to the right, agree=0.658, adj=0.188, (0 split)
##       age        < 49     to the left,  agree=0.632, adj=0.125, (0 split)
## 
## Node number 131015: 22 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5909091  P(node) =0.0011
##     class counts:     1     9     4     7     1
##    probabilities: 0.045 0.409 0.182 0.318 0.045 
##   left son=262030 (8 obs) right son=262031 (14 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=1.2012990, (0 missing)
##       age               < 61     to the right, improve=0.8966589, (0 missing)
##       reimbursement2008 < 53960  to the right, improve=0.8060606, (0 missing)
##       bucket2008        < 4.5    to the right, improve=0.7272727, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.1060606, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 75515  to the right, agree=0.727, adj=0.250, (0 split)
##       age               < 61     to the right, agree=0.682, adj=0.125, (0 split)
## 
## Node number 188792: 18 observations
##   predicted class=B1  expected loss=0.2222222  P(node) =0.0009
##     class counts:    14     4     0     0     0
##    probabilities: 0.778 0.222 0.000 0.000 0.000 
## 
## Node number 188793: 20 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.5  P(node) =0.001
##     class counts:    10     7     2     1     0
##    probabilities: 0.500 0.350 0.100 0.050 0.000 
##   left son=377586 (12 obs) right son=377587 (8 obs)
##   Primary splits:
##       age               < 71.5   to the left,  improve=1.883333, (0 missing)
##       reimbursement2008 < 915    to the left,  improve=1.451515, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.256044, (0 missing)
##   Surrogate splits:
##       arthritis         < 0.5    to the left,  agree=0.7, adj=0.25, (0 split)
##       reimbursement2008 < 930    to the left,  agree=0.7, adj=0.25, (0 split)
## 
## Node number 214076: 12 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0006
##     class counts:     8     2     0     2     0
##    probabilities: 0.667 0.167 0.000 0.167 0.000 
## 
## Node number 214077: 18 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0009
##     class counts:     5     9     2     2     0
##    probabilities: 0.278 0.500 0.111 0.111 0.000 
## 
## Node number 253258: 7 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.00035
##     class counts:     4     2     0     1     0
##    probabilities: 0.571 0.286 0.000 0.143 0.000 
## 
## Node number 253259: 16 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0008
##     class counts:     3     8     4     1     0
##    probabilities: 0.188 0.500 0.250 0.062 0.000 
## 
## Node number 254360: 8 observations
##   predicted class=B1  expected loss=0.375  P(node) =0.0004
##     class counts:     5     0     1     2     0
##    probabilities: 0.625 0.000 0.125 0.250 0.000 
## 
## Node number 254361: 31 observations,    complexity param=0.0002738059
##   predicted class=B2  expected loss=0.5483871  P(node) =0.00155
##     class counts:     9    14     6     2     0
##    probabilities: 0.290 0.452 0.194 0.065 0.000 
##   left son=508722 (9 obs) right son=508723 (22 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=1.6226780, (0 missing)
##       age               < 71.5   to the left,  improve=1.3876390, (0 missing)
##       reimbursement2008 < 7390   to the right, improve=0.9646697, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.8980031, (0 missing)
##       copd              < 0.5    to the right, improve=0.8980031, (0 missing)
## 
## Node number 254364: 7 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.00035
##     class counts:     4     0     2     1     0
##    probabilities: 0.571 0.000 0.286 0.143 0.000 
## 
## Node number 254365: 21 observations,    complexity param=0.0001521144
##   predicted class=B4  expected loss=0.5714286  P(node) =0.00105
##     class counts:     5     6     0     9     1
##    probabilities: 0.238 0.286 0.000 0.429 0.048 
##   left son=508730 (13 obs) right son=508731 (8 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=0.8635531, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6995671, (0 missing)
##       age               < 65.5   to the right, improve=0.5943223, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3571429, (0 missing)
##       reimbursement2008 < 12015  to the right, improve=0.3250916, (0 missing)
##   Surrogate splits:
##       copd              < 0.5    to the left,  agree=0.762, adj=0.375, (0 split)
##       age               < 49     to the right, agree=0.714, adj=0.250, (0 split)
##       reimbursement2008 < 14250  to the left,  agree=0.714, adj=0.250, (0 split)
##       cancer            < 0.5    to the left,  agree=0.667, adj=0.125, (0 split)
## 
## Node number 254366: 25 observations
##   predicted class=B2  expected loss=0.48  P(node) =0.00125
##     class counts:     4    13     3     3     2
##    probabilities: 0.160 0.520 0.120 0.120 0.080 
## 
## Node number 254367: 9 observations
##   predicted class=B4  expected loss=0.4444444  P(node) =0.00045
##     class counts:     1     2     1     5     0
##    probabilities: 0.111 0.222 0.111 0.556 0.000 
## 
## Node number 254758: 19 observations
##   predicted class=B1  expected loss=0.6842105  P(node) =0.00095
##     class counts:     6     4     4     3     2
##    probabilities: 0.316 0.211 0.211 0.158 0.105 
## 
## Node number 254759: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     0     2     4     1     0
##    probabilities: 0.000 0.286 0.571 0.143 0.000 
## 
## Node number 257708: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     0     5     1     1     0
##    probabilities: 0.000 0.714 0.143 0.143 0.000 
## 
## Node number 257709: 27 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5925926  P(node) =0.00135
##     class counts:     1    11    11     3     1
##    probabilities: 0.037 0.407 0.407 0.111 0.037 
##   left son=515418 (19 obs) right son=515419 (8 obs)
##   Primary splits:
##       reimbursement2008 < 9020   to the left,  improve=1.7875240, (0 missing)
##       age               < 70.5   to the left,  improve=0.8518519, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8274318, (0 missing)
##       stroke            < 0.5    to the right, improve=0.4010582, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3909933, (0 missing)
## 
## Node number 262024: 46 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5869565  P(node) =0.0023
##     class counts:     5    19    11     8     3
##    probabilities: 0.109 0.413 0.239 0.174 0.065 
##   left son=524048 (25 obs) right son=524049 (21 obs)
##   Primary splits:
##       reimbursement2008 < 52775  to the right, improve=1.6160660, (0 missing)
##       depression        < 0.5    to the right, improve=1.0500350, (0 missing)
##       bucket2008        < 4.5    to the right, improve=1.0446380, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9895186, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.8413043, (0 missing)
##   Surrogate splits:
##       bucket2008 < 4.5    to the right, agree=0.913, adj=0.810, (0 split)
##       arthritis  < 0.5    to the left,  agree=0.630, adj=0.190, (0 split)
##       depression < 0.5    to the right, agree=0.630, adj=0.190, (0 split)
##       cancer     < 0.5    to the left,  agree=0.587, adj=0.095, (0 split)
##       copd       < 0.5    to the right, agree=0.587, adj=0.095, (0 split)
## 
## Node number 262025: 19 observations
##   predicted class=B4  expected loss=0.5789474  P(node) =0.00095
##     class counts:     4     5     2     8     0
##    probabilities: 0.211 0.263 0.105 0.421 0.000 
## 
## Node number 262028: 16 observations
##   predicted class=B3  expected loss=0.375  P(node) =0.0008
##     class counts:     2     2    10     2     0
##    probabilities: 0.125 0.125 0.625 0.125 0.000 
## 
## Node number 262029: 22 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.6363636  P(node) =0.0011
##     class counts:     0     8     8     5     1
##    probabilities: 0.000 0.364 0.364 0.227 0.045 
##   left son=524058 (12 obs) right son=524059 (10 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=1.5666670, (0 missing)
##       reimbursement2008 < 66505  to the right, improve=1.0000000, (0 missing)
##       age               < 58.5   to the left,  improve=0.9642857, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.6761905, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.4358974, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 67825  to the left,  agree=0.773, adj=0.5, (0 split)
##       age               < 66.5   to the left,  agree=0.682, adj=0.3, (0 split)
##       alzheimers        < 0.5    to the right, agree=0.682, adj=0.3, (0 split)
##       arthritis         < 0.5    to the right, agree=0.591, adj=0.1, (0 split)
##       copd              < 0.5    to the right, agree=0.591, adj=0.1, (0 split)
## 
## Node number 262030: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     1     5     1     1     0
##    probabilities: 0.125 0.625 0.125 0.125 0.000 
## 
## Node number 262031: 14 observations
##   predicted class=B4  expected loss=0.5714286  P(node) =0.0007
##     class counts:     0     4     3     6     1
##    probabilities: 0.000 0.286 0.214 0.429 0.071 
## 
## Node number 377586: 12 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0006
##     class counts:     8     2     1     1     0
##    probabilities: 0.667 0.167 0.083 0.083 0.000 
## 
## Node number 377587: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     2     5     1     0     0
##    probabilities: 0.250 0.625 0.125 0.000 0.000 
## 
## Node number 508722: 9 observations
##   predicted class=B1  expected loss=0.4444444  P(node) =0.00045
##     class counts:     5     2     2     0     0
##    probabilities: 0.556 0.222 0.222 0.000 0.000 
## 
## Node number 508723: 22 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4545455  P(node) =0.0011
##     class counts:     4    12     4     2     0
##    probabilities: 0.182 0.545 0.182 0.091 0.000 
##   left son=1017446 (12 obs) right son=1017447 (10 obs)
##   Primary splits:
##       age               < 71.5   to the left,  improve=1.9848480, (0 missing)
##       reimbursement2008 < 7425   to the right, improve=1.2086580, (0 missing)
##       depression        < 0.5    to the right, improve=1.1002330, (0 missing)
##       copd              < 0.5    to the right, improve=0.9967532, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.6753247, (0 missing)
##   Surrogate splits:
##       depression        < 0.5    to the right, agree=0.682, adj=0.3, (0 split)
##       copd              < 0.5    to the right, agree=0.636, adj=0.2, (0 split)
##       ihd               < 0.5    to the right, agree=0.636, adj=0.2, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.636, adj=0.2, (0 split)
##       reimbursement2008 < 7010   to the right, agree=0.636, adj=0.2, (0 split)
## 
## Node number 508730: 13 observations
##   predicted class=B2  expected loss=0.6153846  P(node) =0.00065
##     class counts:     3     5     0     4     1
##    probabilities: 0.231 0.385 0.000 0.308 0.077 
## 
## Node number 508731: 8 observations
##   predicted class=B4  expected loss=0.375  P(node) =0.0004
##     class counts:     2     1     0     5     0
##    probabilities: 0.250 0.125 0.000 0.625 0.000 
## 
## Node number 515418: 19 observations
##   predicted class=B2  expected loss=0.5263158  P(node) =0.00095
##     class counts:     1     9     5     3     1
##    probabilities: 0.053 0.474 0.263 0.158 0.053 
## 
## Node number 515419: 8 observations
##   predicted class=B3  expected loss=0.25  P(node) =0.0004
##     class counts:     0     2     6     0     0
##    probabilities: 0.000 0.250 0.750 0.000 0.000 
## 
## Node number 524048: 25 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.64  P(node) =0.00125
##     class counts:     4     9     9     2     1
##    probabilities: 0.160 0.360 0.360 0.080 0.040 
##   left son=1048096 (11 obs) right son=1048097 (14 obs)
##   Primary splits:
##       reimbursement2008 < 59785  to the right, improve=2.4722080, (0 missing)
##       age               < 76.5   to the right, improve=0.7825641, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.5466667, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2682353, (0 missing)
##       depression        < 0.5    to the right, improve=0.1561905, (0 missing)
##   Surrogate splits:
##       age        < 79.5   to the right, agree=0.64, adj=0.182, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.64, adj=0.182, (0 split)
##       cancer     < 0.5    to the right, agree=0.64, adj=0.182, (0 split)
##       depression < 0.5    to the left,  agree=0.60, adj=0.091, (0 split)
##       bucket2008 < 4.5    to the right, agree=0.60, adj=0.091, (0 split)
## 
## Node number 524049: 21 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5238095  P(node) =0.00105
##     class counts:     1    10     2     6     2
##    probabilities: 0.048 0.476 0.095 0.286 0.095 
##   left son=1048098 (7 obs) right son=1048099 (14 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=1.9523810, (0 missing)
##       depression        < 0.5    to the left,  improve=1.1316020, (0 missing)
##       reimbursement2008 < 41140  to the left,  improve=1.0760070, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.4043290, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2875458, (0 missing)
##   Surrogate splits:
##       age               < 78.5   to the right, agree=0.810, adj=0.429, (0 split)
##       reimbursement2008 < 40060  to the left,  agree=0.762, adj=0.286, (0 split)
## 
## Node number 524058: 12 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0006
##     class counts:     0     6     2     3     1
##    probabilities: 0.000 0.500 0.167 0.250 0.083 
## 
## Node number 524059: 10 observations
##   predicted class=B3  expected loss=0.4  P(node) =0.0005
##     class counts:     0     2     6     2     0
##    probabilities: 0.000 0.200 0.600 0.200 0.000 
## 
## Node number 1017446: 12 observations
##   predicted class=B2  expected loss=0.25  P(node) =0.0006
##     class counts:     2     9     0     1     0
##    probabilities: 0.167 0.750 0.000 0.083 0.000 
## 
## Node number 1017447: 10 observations
##   predicted class=B3  expected loss=0.6  P(node) =0.0005
##     class counts:     2     3     4     1     0
##    probabilities: 0.200 0.300 0.400 0.100 0.000 
## 
## Node number 1048096: 11 observations
##   predicted class=B1  expected loss=0.6363636  P(node) =0.00055
##     class counts:     4     4     1     2     0
##    probabilities: 0.364 0.364 0.091 0.182 0.000 
## 
## Node number 1048097: 14 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.0007
##     class counts:     0     5     8     0     1
##    probabilities: 0.000 0.357 0.571 0.000 0.071 
## 
## Node number 1048098: 7 observations
##   predicted class=B2  expected loss=0.1428571  P(node) =0.00035
##     class counts:     0     6     0     1     0
##    probabilities: 0.000 0.857 0.000 0.143 0.000 
## 
## Node number 1048099: 14 observations
##   predicted class=B4  expected loss=0.6428571  P(node) =0.0007
##     class counts:     1     4     2     5     2
##    probabilities: 0.071 0.286 0.143 0.357 0.143 
## 
## n= 20000 
## 
## node), split, n, loss, yval, (yprob)
##       * denotes terminal node
## 
##       1) root 20000 6574 B1 (0.67 0.19 0.089 0.043 0.0057)  
##         2) reimbursement2008< 1565 12142 1549 B1 (0.87 0.077 0.036 0.014 0.0016)  
##           4) reimbursement2008< 195 6456  205 B1 (0.97 0.017 0.011 0.0039 0.00046) *
##           5) reimbursement2008>=195 5686 1344 B1 (0.76 0.15 0.064 0.024 0.0028)  
##            10) reimbursement2008< 685 2374  402 B1 (0.83 0.1 0.052 0.015 0.0021)  
##              20) diabetes< 0.5 1860  289 B1 (0.84 0.095 0.046 0.012 0.0022)  
##                40) age< 89.5 1774  266 B1 (0.85 0.093 0.042 0.013 0.0017)  
##                  80) age>=29.5 1764  262 B1 (0.85 0.092 0.043 0.012 0.0017)  
##                   160) osteoporosis< 0.5 1586  227 B1 (0.86 0.086 0.043 0.012 0.0019)  
##                     320) age< 71.5 756   92 B1 (0.88 0.075 0.036 0.0093 0.0013) *
##                     321) age>=71.5 830  135 B1 (0.84 0.096 0.049 0.014 0.0024)  
##                       642) reimbursement2008< 665 801  127 B1 (0.84 0.091 0.05 0.015 0.0025)  
##                        1284) reimbursement2008< 245 94   10 B1 (0.89 0.053 0.043 0.011 0) *
##                        1285) reimbursement2008>=245 707  117 B1 (0.83 0.096 0.051 0.016 0.0028)  
##                          2570) reimbursement2008>=495 277   38 B1 (0.86 0.076 0.036 0.025 0) *
##                          2571) reimbursement2008< 495 430   79 B1 (0.82 0.11 0.06 0.0093 0.0047)  
##                            5142) reimbursement2008< 475 398   70 B1 (0.82 0.098 0.065 0.0075 0.005)  
##                             10284) ihd< 0.5 321   52 B1 (0.84 0.087 0.059 0.0093 0.0062) *
##                             10285) ihd>=0.5 77   18 B1 (0.77 0.14 0.091 0 0)  
##                               20570) age< 86.5 70   12 B1 (0.83 0.1 0.071 0 0) *
##                               20571) age>=86.5 7    3 B2 (0.14 0.57 0.29 0 0) *
##                            5143) reimbursement2008>=475 32    9 B1 (0.72 0.25 0 0.031 0)  
##                             10286) age>=83.5 10    1 B1 (0.9 0.1 0 0 0) *
##                             10287) age< 83.5 22    8 B1 (0.64 0.32 0 0.045 0)  
##                               20574) age< 78.5 14    2 B1 (0.86 0.14 0 0 0) *
##                               20575) age>=78.5 8    3 B2 (0.25 0.62 0 0.12 0) *
##                       643) reimbursement2008>=665 29    8 B1 (0.72 0.24 0.034 0 0) *
##                   161) osteoporosis>=0.5 178   35 B1 (0.8 0.14 0.039 0.017 0)  
##                     322) reimbursement2008>=225 171   31 B1 (0.82 0.12 0.041 0.018 0) *
##                     323) reimbursement2008< 225 7    3 B2 (0.43 0.57 0 0 0) *
##                  81) age< 29.5 10    4 B1 (0.6 0.3 0 0.1 0) *
##                41) age>=89.5 86   23 B1 (0.73 0.13 0.13 0 0.012) *
##              21) diabetes>=0.5 514  113 B1 (0.78 0.12 0.072 0.023 0.0019)  
##                42) reimbursement2008< 425 173   28 B1 (0.84 0.075 0.064 0.023 0)  
##                  84) age>=64.5 147   18 B1 (0.88 0.061 0.048 0.014 0) *
##                  85) age< 64.5 26   10 B1 (0.62 0.15 0.15 0.077 0)  
##                   170) reimbursement2008>=250 19    5 B1 (0.74 0.11 0.053 0.11 0) *
##                   171) reimbursement2008< 250 7    4 B3 (0.29 0.29 0.43 0 0) *
##                43) reimbursement2008>=425 341   85 B1 (0.75 0.15 0.076 0.023 0.0029) *
##            11) reimbursement2008>=685 3312  942 B1 (0.72 0.18 0.073 0.031 0.0033)  
##              22) ihd< 0.5 1722  424 B1 (0.75 0.15 0.062 0.03 0.0029)  
##                44) reimbursement2008< 1085 951  209 B1 (0.78 0.14 0.05 0.027 0.0032)  
##                  88) alzheimers< 0.5 811  169 B1 (0.79 0.13 0.047 0.03 0.0025)  
##                   176) diabetes< 0.5 544  105 B1 (0.81 0.11 0.048 0.031 0.0037)  
##                     352) reimbursement2008< 905 338   59 B1 (0.83 0.086 0.059 0.024 0.0059) *
##                     353) reimbursement2008>=905 206   46 B1 (0.78 0.15 0.029 0.044 0)  
##                       706) reimbursement2008>=955 149   25 B1 (0.83 0.12 0.02 0.027 0) *
##                       707) reimbursement2008< 955 57   21 B1 (0.63 0.23 0.053 0.088 0)  
##                        1414) age< 83.5 43   12 B1 (0.72 0.14 0.07 0.07 0) *
##                        1415) age>=83.5 14    7 B2 (0.36 0.5 0 0.14 0) *
##                   177) diabetes>=0.5 267   64 B1 (0.76 0.17 0.045 0.026 0)  
##                     354) reimbursement2008>=795 182   38 B1 (0.79 0.13 0.049 0.027 0) *
##                     355) reimbursement2008< 795 85   26 B1 (0.69 0.25 0.035 0.024 0)  
##                       710) reimbursement2008< 785 76   21 B1 (0.72 0.21 0.039 0.026 0)  
##                        1420) age>=81 9    1 B1 (0.89 0 0 0.11 0) *
##                        1421) age< 81 67   20 B1 (0.7 0.24 0.045 0.015 0)  
##                          2842) age< 78.5 60   16 B1 (0.73 0.2 0.05 0.017 0) *
##                          2843) age>=78.5 7    3 B2 (0.43 0.57 0 0 0) *
##                       711) reimbursement2008>=785 9    4 B2 (0.44 0.56 0 0 0) *
##                  89) alzheimers>=0.5 140   40 B1 (0.71 0.19 0.071 0.014 0.0071)  
##                   178) age< 91.5 133   35 B1 (0.74 0.18 0.068 0.0075 0.0075) *
##                   179) age>=91.5 7    4 B2 (0.29 0.43 0.14 0.14 0) *
##                45) reimbursement2008>=1085 771  215 B1 (0.72 0.17 0.077 0.032 0.0026)  
##                  90) stroke< 0.5 758  207 B1 (0.73 0.17 0.071 0.033 0.0026)  
##                   180) osteoporosis< 0.5 586  150 B1 (0.74 0.15 0.073 0.032 0)  
##                     360) age>=67.5 449  107 B1 (0.76 0.13 0.08 0.031 0)  
##                       720) reimbursement2008< 1335 283   60 B1 (0.79 0.1 0.078 0.032 0)  
##                        1440) age>=87.5 27    2 B1 (0.93 0.037 0.037 0 0) *
##                        1441) age< 87.5 256   58 B1 (0.77 0.11 0.082 0.035 0)  
##                          2882) age< 80.5 197   38 B1 (0.81 0.091 0.066 0.036 0) *
##                          2883) age>=80.5 59   20 B1 (0.66 0.17 0.14 0.034 0)  
##                            5766) reimbursement2008>=1115 51   15 B1 (0.71 0.12 0.14 0.039 0) *
##                            5767) reimbursement2008< 1115 8    4 B2 (0.38 0.5 0.12 0 0) *
##                       721) reimbursement2008>=1335 166   47 B1 (0.72 0.17 0.084 0.03 0)  
##                        1442) copd< 0.5 158   43 B1 (0.73 0.16 0.082 0.032 0)  
##                          2884) age>=73.5 109   31 B1 (0.72 0.19 0.083 0.0092 0)  
##                            5768) age>=77.5 79   18 B1 (0.77 0.14 0.076 0.013 0) *
##                            5769) age< 77.5 30   13 B1 (0.57 0.33 0.1 0 0)  
##                             11538) arthritis< 0.5 23    8 B1 (0.65 0.22 0.13 0 0) *
##                             11539) arthritis>=0.5 7    2 B2 (0.29 0.71 0 0 0) *
##                          2885) age< 73.5 49   12 B1 (0.76 0.082 0.082 0.082 0) *
##                        1443) copd>=0.5 8    4 B1 (0.5 0.38 0.12 0 0) *
##                     361) age< 67.5 137   43 B1 (0.69 0.23 0.051 0.036 0)  
##                       722) reimbursement2008>=1345 50   13 B1 (0.74 0.14 0.08 0.04 0) *
##                       723) reimbursement2008< 1345 87   30 B1 (0.66 0.28 0.034 0.034 0)  
##                        1446) reimbursement2008< 1235 52   15 B1 (0.71 0.19 0.038 0.058 0)  
##                          2892) reimbursement2008>=1155 32    6 B1 (0.81 0.12 0.031 0.031 0) *
##                          2893) reimbursement2008< 1155 20    9 B1 (0.55 0.3 0.05 0.1 0)  
##                            5786) reimbursement2008< 1115 9    2 B1 (0.78 0.11 0 0.11 0) *
##                            5787) reimbursement2008>=1115 11    6 B2 (0.36 0.45 0.091 0.091 0) *
##                        1447) reimbursement2008>=1235 35   15 B1 (0.57 0.4 0.029 0 0)  
##                          2894) diabetes>=0.5 15    4 B1 (0.73 0.2 0.067 0 0) *
##                          2895) diabetes< 0.5 20    9 B2 (0.45 0.55 0 0 0)  
##                            5790) reimbursement2008>=1275 11    5 B1 (0.55 0.45 0 0 0) *
##                            5791) reimbursement2008< 1275 9    3 B2 (0.33 0.67 0 0 0) *
##                   181) osteoporosis>=0.5 172   57 B1 (0.67 0.22 0.064 0.035 0.012)  
##                     362) age< 83.5 143   42 B1 (0.71 0.2 0.056 0.028 0.014)  
##                       724) age>=75.5 44    8 B1 (0.82 0.11 0.023 0.023 0.023) *
##                       725) age< 75.5 99   34 B1 (0.66 0.23 0.071 0.03 0.01)  
##                        1450) age< 73.5 88   26 B1 (0.7 0.19 0.057 0.034 0.011) *
##                        1451) age>=73.5 11    5 B2 (0.27 0.55 0.18 0 0) *
##                     363) age>=83.5 29   15 B1 (0.48 0.34 0.1 0.069 0)  
##                       726) diabetes< 0.5 17    6 B1 (0.65 0.24 0.059 0.059 0) *
##                       727) diabetes>=0.5 12    6 B2 (0.25 0.5 0.17 0.083 0) *
##                  91) stroke>=0.5 13    8 B1 (0.38 0.23 0.38 0 0) *
##              23) ihd>=0.5 1590  518 B1 (0.67 0.2 0.084 0.033 0.0038)  
##                46) diabetes< 0.5 771  220 B1 (0.71 0.18 0.078 0.022 0.0052)  
##                  92) kidney< 0.5 713  194 B1 (0.73 0.18 0.072 0.02 0.0056)  
##                   184) age>=39.5 691  184 B1 (0.73 0.17 0.072 0.019 0.0029)  
##                     368) reimbursement2008< 1465 628  161 B1 (0.74 0.17 0.068 0.019 0.0032)  
##                       736) heart.failure< 0.5 455  105 B1 (0.77 0.15 0.057 0.015 0.0044) *
##                       737) heart.failure>=0.5 173   56 B1 (0.68 0.2 0.098 0.029 0)  
##                        1474) reimbursement2008>=820 145   41 B1 (0.72 0.17 0.09 0.021 0)  
##                          2948) age< 51 8    0 B1 (1 0 0 0 0) *
##                          2949) age>=51 137   41 B1 (0.7 0.18 0.095 0.022 0)  
##                            5898) copd>=0.5 10    1 B1 (0.9 0 0.1 0 0) *
##                            5899) copd< 0.5 127   40 B1 (0.69 0.2 0.094 0.024 0)  
##                             11798) reimbursement2008< 875 8    1 B1 (0.88 0 0.12 0 0) *
##                             11799) reimbursement2008>=875 119   39 B1 (0.67 0.21 0.092 0.025 0)  
##                               23598) reimbursement2008>=1125 63   18 B1 (0.71 0.16 0.13 0 0) *
##                               23599) reimbursement2008< 1125 56   21 B1 (0.62 0.27 0.054 0.054 0)  
##                                 47198) age< 80.5 48   16 B1 (0.67 0.23 0.062 0.042 0)  
##                                   94396) age< 74.5 38   14 B1 (0.63 0.29 0.053 0.026 0)  
##                                    188792) reimbursement2008>=975 18    4 B1 (0.78 0.22 0 0 0) *
##                                    188793) reimbursement2008< 975 20   10 B1 (0.5 0.35 0.1 0.05 0)  
##                                      377586) age< 71.5 12    4 B1 (0.67 0.17 0.083 0.083 0) *
##                                      377587) age>=71.5 8    3 B2 (0.25 0.62 0.12 0 0) *
##                                   94397) age>=74.5 10    2 B1 (0.8 0 0.1 0.1 0) *
##                                 47199) age>=80.5 8    4 B2 (0.38 0.5 0 0.12 0) *
##                        1475) reimbursement2008< 820 28   15 B1 (0.46 0.32 0.14 0.071 0)  
##                          2950) age>=78.5 8    2 B1 (0.75 0.12 0 0.12 0) *
##                          2951) age< 78.5 20   12 B2 (0.35 0.4 0.2 0.05 0)  
##                            5902) age< 66.5 7    4 B1 (0.43 0.29 0.29 0 0) *
##                            5903) age>=66.5 13    7 B2 (0.31 0.46 0.15 0.077 0) *
##                     369) reimbursement2008>=1465 63   23 B1 (0.63 0.24 0.11 0.016 0)  
##                       738) reimbursement2008>=1485 52   16 B1 (0.69 0.19 0.096 0.019 0) *
##                       739) reimbursement2008< 1485 11    6 B2 (0.36 0.45 0.18 0 0) *
##                   185) age< 39.5 22   10 B1 (0.55 0.27 0.045 0.045 0.091) *
##                  93) kidney>=0.5 58   26 B1 (0.55 0.24 0.16 0.052 0)  
##                   186) age< 69.5 15    2 B1 (0.87 0 0.13 0 0) *
##                   187) age>=69.5 43   24 B1 (0.44 0.33 0.16 0.07 0)  
##                     374) reimbursement2008< 1355 35   17 B1 (0.51 0.26 0.14 0.086 0)  
##                       748) reimbursement2008>=895 28   12 B1 (0.57 0.25 0.071 0.11 0) *
##                       749) reimbursement2008< 895 7    4 B3 (0.29 0.29 0.43 0 0) *
##                     375) reimbursement2008>=1355 8    3 B2 (0.12 0.62 0.25 0 0) *
##                47) diabetes>=0.5 819  298 B1 (0.64 0.23 0.09 0.044 0.0024)  
##                  94) reimbursement2008< 1155 412  126 B1 (0.69 0.19 0.083 0.029 0.0024)  
##                   188) osteoporosis>=0.5 90   19 B1 (0.79 0.11 0.078 0.022 0) *
##                   189) osteoporosis< 0.5 322  107 B1 (0.67 0.21 0.084 0.031 0.0031)  
##                     378) age>=46.5 310   99 B1 (0.68 0.21 0.077 0.029 0.0032)  
##                       756) reimbursement2008>=835 213   61 B1 (0.71 0.19 0.08 0.014 0.0047)  
##                        1512) age>=79.5 74   17 B1 (0.77 0.12 0.068 0.041 0) *
##                        1513) age< 79.5 139   44 B1 (0.68 0.22 0.086 0 0.0072)  
##                          3026) reimbursement2008>=1105 14    1 B1 (0.93 0.071 0 0 0) *
##                          3027) reimbursement2008< 1105 125   43 B1 (0.66 0.24 0.096 0 0.008)  
##                            6054) arthritis>=0.5 10    1 B1 (0.9 0.1 0 0 0) *
##                            6055) arthritis< 0.5 115   42 B1 (0.63 0.25 0.1 0 0.0087)  
##                             12110) age>=73.5 36   14 B1 (0.61 0.36 0.028 0 0)  
##                               24220) reimbursement2008< 1005 28    9 B1 (0.68 0.29 0.036 0 0) *
##                               24221) reimbursement2008>=1005 8    3 B2 (0.38 0.62 0 0 0) *
##                             12111) age< 73.5 79   28 B1 (0.65 0.2 0.14 0 0.013)  
##                               24222) age< 71.5 65   24 B1 (0.63 0.25 0.11 0 0.015)  
##                                 48444) reimbursement2008< 1075 58   20 B1 (0.66 0.21 0.12 0 0.017) *
##                                 48445) reimbursement2008>=1075 7    3 B2 (0.43 0.57 0 0 0) *
##                               24223) age>=71.5 14    4 B1 (0.71 0 0.29 0 0) *
##                       757) reimbursement2008< 835 97   38 B1 (0.61 0.26 0.072 0.062 0)  
##                        1514) age< 80.5 68   23 B1 (0.66 0.19 0.074 0.074 0)  
##                          3028) kidney>=0.5 9    4 B2 (0.44 0.56 0 0 0) *
##                          3029) kidney< 0.5 59   18 B1 (0.69 0.14 0.085 0.085 0) *
##                        1515) age>=80.5 29   15 B1 (0.48 0.41 0.069 0.034 0)  
##                          3030) age>=83.5 20    9 B1 (0.55 0.35 0.05 0.05 0) *
##                          3031) age< 83.5 9    4 B2 (0.33 0.56 0.11 0 0) *
##                     379) age< 46.5 12    8 B1 (0.33 0.33 0.25 0.083 0) *
##                  95) reimbursement2008>=1155 407  172 B1 (0.58 0.26 0.098 0.059 0.0025)  
##                   190) age< 89.5 382  155 B1 (0.59 0.25 0.094 0.058 0.0026)  
##                     380) reimbursement2008>=1175 352  141 B1 (0.6 0.26 0.085 0.051 0)  
##                       760) depression< 0.5 242   90 B1 (0.63 0.27 0.054 0.05 0) *
##                       761) depression>=0.5 110   51 B1 (0.54 0.25 0.15 0.055 0)  
##                        1522) age< 70.5 54   20 B1 (0.63 0.19 0.11 0.074 0) *
##                        1523) age>=70.5 56   31 B1 (0.45 0.32 0.2 0.036 0)  
##                          3046) age>=76.5 31   14 B1 (0.55 0.16 0.23 0.065 0) *
##                          3047) age< 76.5 25   12 B2 (0.32 0.52 0.16 0 0)  
##                            6094) reimbursement2008< 1435 18    8 B2 (0.44 0.56 0 0 0) *
##                            6095) reimbursement2008>=1435 7    3 B3 (0 0.43 0.57 0 0) *
##                     381) reimbursement2008< 1175 30   14 B1 (0.53 0.1 0.2 0.13 0.033)  
##                       762) age>=70 22    8 B1 (0.64 0.091 0.18 0.045 0.045) *
##                       763) age< 70 8    5 B4 (0.25 0.12 0.25 0.38 0) *
##                   191) age>=89.5 25   14 B2 (0.32 0.44 0.16 0.08 0)  
##                     382) depression>=0.5 7    2 B1 (0.71 0.14 0.14 0 0) *
##                     383) depression< 0.5 18    8 B2 (0.17 0.56 0.17 0.11 0) *
##         3) reimbursement2008>=1565 7858 4988 B2 (0.36 0.37 0.17 0.089 0.012)  
##           6) reimbursement2008< 3425 3262 1635 B1 (0.5 0.32 0.13 0.048 0.0049)  
##            12) ihd< 0.5 1087  442 B1 (0.59 0.26 0.11 0.033 0.0037)  
##              24) kidney< 0.5 941  358 B1 (0.62 0.24 0.1 0.031 0.0043)  
##                48) heart.failure< 0.5 680  234 B1 (0.66 0.23 0.087 0.029 0.0029)  
##                  96) reimbursement2008< 2605 524  172 B1 (0.67 0.2 0.099 0.031 0.0019)  
##                   192) age< 96.5 517  167 B1 (0.68 0.19 0.097 0.031 0.0019)  
##                     384) depression< 0.5 395  119 B1 (0.7 0.18 0.099 0.023 0.0025)  
##                       768) age>=68.5 288   79 B1 (0.73 0.15 0.097 0.028 0)  
##                        1536) arthritis>=0.5 47   11 B1 (0.77 0.064 0.17 0 0)  
##                          3072) reimbursement2008>=1655 40    7 B1 (0.82 0.075 0.1 0 0) *
##                          3073) reimbursement2008< 1655 7    3 B3 (0.43 0 0.57 0 0) *
##                        1537) arthritis< 0.5 241   68 B1 (0.72 0.17 0.083 0.033 0) *
##                       769) age< 68.5 107   40 B1 (0.63 0.25 0.1 0.0093 0.0093)  
##                        1538) arthritis< 0.5 92   31 B1 (0.66 0.24 0.076 0.011 0.011)  
##                          3076) osteoporosis>=0.5 23    5 B1 (0.78 0.13 0.043 0.043 0) *
##                          3077) osteoporosis< 0.5 69   26 B1 (0.62 0.28 0.087 0 0.014)  
##                            6154) reimbursement2008< 2295 59   20 B1 (0.66 0.25 0.068 0 0.017)  
##                             12308) reimbursement2008>=2050 15    2 B1 (0.87 0.13 0 0 0) *
##                             12309) reimbursement2008< 2050 44   18 B1 (0.59 0.3 0.091 0 0.023)  
##                               24618) diabetes>=0.5 16    4 B1 (0.75 0.12 0.12 0 0) *
##                               24619) diabetes< 0.5 28   14 B1 (0.5 0.39 0.071 0 0.036)  
##                                 49238) reimbursement2008< 1880 20    7 B1 (0.65 0.35 0 0 0) *
##                                 49239) reimbursement2008>=1880 8    4 B2 (0.12 0.5 0.25 0 0.12) *
##                            6155) reimbursement2008>=2295 10    6 B1 (0.4 0.4 0.2 0 0) *
##                        1539) arthritis>=0.5 15    9 B1 (0.4 0.33 0.27 0 0) *
##                     385) depression>=0.5 122   48 B1 (0.61 0.25 0.09 0.057 0)  
##                       770) age< 64 22    2 B1 (0.91 0.091 0 0 0) *
##                       771) age>=64 100   46 B1 (0.54 0.28 0.11 0.07 0)  
##                        1542) age< 79.5 72   29 B1 (0.6 0.29 0.083 0.028 0)  
##                          3084) arthritis< 0.5 58   24 B1 (0.59 0.34 0.069 0 0)  
##                            6168) reimbursement2008< 2415 49   19 B1 (0.61 0.31 0.082 0 0)  
##                             12336) reimbursement2008>=2155 11    2 B1 (0.82 0.18 0 0 0) *
##                             12337) reimbursement2008< 2155 38   17 B1 (0.55 0.34 0.11 0 0)  
##                               24674) reimbursement2008< 2020 29   11 B1 (0.62 0.31 0.069 0 0) *
##                               24675) reimbursement2008>=2020 9    5 B2 (0.33 0.44 0.22 0 0) *
##                            6169) reimbursement2008>=2415 9    4 B2 (0.44 0.56 0 0 0) *
##                          3085) arthritis>=0.5 14    5 B1 (0.64 0.071 0.14 0.14 0) *
##                        1543) age>=79.5 28   17 B1 (0.39 0.25 0.18 0.18 0)  
##                          3086) arthritis>=0.5 7    2 B1 (0.71 0.14 0 0.14 0) *
##                          3087) arthritis< 0.5 21   15 B1 (0.29 0.29 0.24 0.19 0)  
##                            6174) reimbursement2008< 2170 13    8 B2 (0.31 0.38 0.23 0.077 0) *
##                            6175) reimbursement2008>=2170 8    5 B4 (0.25 0.12 0.25 0.38 0) *
##                   193) age>=96.5 7    4 B2 (0.29 0.43 0.29 0 0) *
##                  97) reimbursement2008>=2605 156   62 B1 (0.6 0.32 0.045 0.026 0.0064)  
##                   194) arthritis< 0.5 118   40 B1 (0.66 0.26 0.051 0.017 0.0085)  
##                     388) age< 69.5 45   11 B1 (0.76 0.18 0.044 0.022 0) *
##                     389) age>=69.5 73   29 B1 (0.6 0.32 0.055 0.014 0.014)  
##                       778) reimbursement2008< 3390 66   27 B1 (0.59 0.35 0.045 0 0.015)  
##                        1556) age< 80.5 41   17 B1 (0.59 0.41 0 0 0)  
##                          3112) reimbursement2008>=2765 30   10 B1 (0.67 0.33 0 0 0)  
##                            6224) age< 77.5 23    5 B1 (0.78 0.22 0 0 0) *
##                            6225) age>=77.5 7    2 B2 (0.29 0.71 0 0 0) *
##                          3113) reimbursement2008< 2765 11    4 B2 (0.36 0.64 0 0 0) *
##                        1557) age>=80.5 25   10 B1 (0.6 0.24 0.12 0 0.04)  
##                          3114) reimbursement2008< 3090 18    5 B1 (0.72 0.11 0.17 0 0) *
##                          3115) reimbursement2008>=3090 7    3 B2 (0.29 0.57 0 0 0.14) *
##                       779) reimbursement2008>=3390 7    2 B1 (0.71 0 0.14 0.14 0) *
##                   195) arthritis>=0.5 38   19 B2 (0.42 0.5 0.026 0.053 0)  
##                     390) diabetes< 0.5 12    4 B1 (0.67 0.25 0 0.083 0) *
##                     391) diabetes>=0.5 26   10 B2 (0.31 0.62 0.038 0.038 0)  
##                       782) depression>=0.5 7    3 B1 (0.57 0.43 0 0 0) *
##                       783) depression< 0.5 19    6 B2 (0.21 0.68 0.053 0.053 0) *
##                49) heart.failure>=0.5 261  124 B1 (0.52 0.29 0.14 0.034 0.0077)  
##                  98) diabetes< 0.5 110   42 B1 (0.62 0.24 0.082 0.055 0.0091)  
##                   196) depression>=0.5 32    8 B1 (0.75 0.12 0.12 0 0) *
##                   197) depression< 0.5 78   34 B1 (0.56 0.28 0.064 0.077 0.013)  
##                     394) reimbursement2008>=2685 20    5 B1 (0.75 0.15 0 0.1 0) *
##                     395) reimbursement2008< 2685 58   29 B1 (0.5 0.33 0.086 0.069 0.017)  
##                       790) reimbursement2008< 2425 50   23 B1 (0.54 0.32 0.04 0.08 0.02)  
##                        1580) age>=71.5 26    9 B1 (0.65 0.27 0.038 0 0.038) *
##                        1581) age< 71.5 24   14 B1 (0.42 0.38 0.042 0.17 0)  
##                          3162) age< 68.5 17    8 B1 (0.53 0.29 0.059 0.12 0) *
##                          3163) age>=68.5 7    3 B2 (0.14 0.57 0 0.29 0) *
##                       791) reimbursement2008>=2425 8    5 B2 (0.25 0.38 0.38 0 0) *
##                  99) diabetes>=0.5 151   82 B1 (0.46 0.33 0.19 0.02 0.0066)  
##                   198) reimbursement2008>=1675 140   74 B1 (0.47 0.31 0.19 0.021 0.0071)  
##                     396) reimbursement2008< 1775 10    3 B1 (0.7 0 0.3 0 0) *
##                     397) reimbursement2008>=1775 130   71 B1 (0.45 0.33 0.18 0.023 0.0077)  
##                       794) reimbursement2008>=3265 9    2 B1 (0.78 0.11 0.11 0 0) *
##                       795) reimbursement2008< 3265 121   69 B1 (0.43 0.35 0.19 0.025 0.0083)  
##                        1590) reimbursement2008< 3190 113   62 B1 (0.45 0.33 0.19 0.027 0.0088)  
##                          3180) reimbursement2008>=3055 8    1 B1 (0.88 0 0 0.12 0) *
##                          3181) reimbursement2008< 3055 105   61 B1 (0.42 0.35 0.2 0.019 0.0095)  
##                            6362) age>=75.5 45   22 B1 (0.51 0.29 0.18 0 0.022)  
##                             12724) arthritis< 0.5 32   13 B1 (0.59 0.19 0.19 0 0.031) *
##                             12725) arthritis>=0.5 13    6 B2 (0.31 0.54 0.15 0 0) *
##                            6363) age< 75.5 60   36 B2 (0.35 0.4 0.22 0.033 0)  
##                             12726) reimbursement2008>=2215 36   20 B1 (0.44 0.28 0.22 0.056 0)  
##                               25452) reimbursement2008< 2400 12    5 B1 (0.58 0.083 0.33 0 0) *
##                               25453) reimbursement2008>=2400 24   15 B1 (0.38 0.38 0.17 0.083 0)  
##                                 50906) age< 70 16    9 B2 (0.38 0.44 0.19 0 0) *
##                                 50907) age>=70 8    5 B1 (0.38 0.25 0.12 0.25 0) *
##                             12727) reimbursement2008< 2215 24   10 B2 (0.21 0.58 0.21 0 0) *
##                        1591) reimbursement2008>=3190 8    3 B2 (0.12 0.62 0.25 0 0) *
##                   199) reimbursement2008< 1675 11    4 B2 (0.27 0.64 0.091 0 0) *
##              25) kidney>=0.5 146   84 B1 (0.42 0.34 0.18 0.048 0)  
##                50) age< 74.5 82   38 B1 (0.54 0.27 0.15 0.049 0)  
##                 100) age>=63.5 63   25 B1 (0.6 0.19 0.14 0.063 0) *
##                 101) age< 63.5 19    9 B2 (0.32 0.53 0.16 0 0) *
##                51) age>=74.5 64   36 B2 (0.28 0.44 0.23 0.047 0)  
##                 102) age>=84.5 28   12 B2 (0.32 0.57 0.071 0.036 0) *
##                 103) age< 84.5 36   23 B3 (0.25 0.33 0.36 0.056 0)  
##                   206) reimbursement2008< 1990 10    4 B1 (0.6 0.2 0.2 0 0) *
##                   207) reimbursement2008>=1990 26   15 B3 (0.12 0.38 0.42 0.077 0)  
##                     414) age< 78.5 12    5 B2 (0.17 0.58 0.17 0.083 0) *
##                     415) age>=78.5 14    5 B3 (0.071 0.21 0.64 0.071 0) *
##            13) ihd>=0.5 2175 1193 B1 (0.45 0.35 0.13 0.055 0.0055)  
##              26) reimbursement2008< 2515 1275  637 B1 (0.5 0.32 0.12 0.053 0.0063)  
##                52) depression< 0.5 880  412 B1 (0.53 0.29 0.12 0.052 0.008)  
##                 104) stroke< 0.5 849  390 B1 (0.54 0.29 0.11 0.053 0.0082)  
##                   208) age>=73.5 406  162 B1 (0.6 0.26 0.086 0.047 0.0074)  
##                     416) arthritis< 0.5 307  115 B1 (0.63 0.23 0.091 0.046 0.0065)  
##                       832) diabetes>=0.5 163   55 B1 (0.66 0.17 0.11 0.049 0.0061) *
##                       833) diabetes< 0.5 144   60 B1 (0.58 0.3 0.069 0.042 0.0069)  
##                        1666) heart.failure< 0.5 86   31 B1 (0.64 0.22 0.081 0.047 0.012)  
##                          3332) alzheimers< 0.5 70   21 B1 (0.7 0.17 0.071 0.043 0.014) *
##                          3333) alzheimers>=0.5 16    9 B2 (0.38 0.44 0.12 0.062 0) *
##                        1667) heart.failure>=0.5 58   29 B1 (0.5 0.41 0.052 0.034 0)  
##                          3334) age< 75.5 8    2 B1 (0.75 0.12 0.12 0 0) *
##                          3335) age>=75.5 50   27 B1 (0.46 0.46 0.04 0.04 0)  
##                            6670) age< 89.5 42   21 B1 (0.5 0.43 0.048 0.024 0)  
##                             13340) reimbursement2008< 2305 34   15 B1 (0.56 0.41 0.029 0 0)  
##                               26680) reimbursement2008>=2070 7    2 B1 (0.71 0.14 0.14 0 0) *
##                               26681) reimbursement2008< 2070 27   13 B1 (0.52 0.48 0 0 0)  
##                                 53362) age>=79.5 20    8 B1 (0.6 0.4 0 0 0)  
##                                  106724) reimbursement2008< 1790 9    2 B1 (0.78 0.22 0 0 0) *
##                                  106725) reimbursement2008>=1790 11    5 B2 (0.45 0.55 0 0 0) *
##                                 53363) age< 79.5 7    2 B2 (0.29 0.71 0 0 0) *
##                             13341) reimbursement2008>=2305 8    4 B2 (0.25 0.5 0.12 0.12 0) *
##                            6671) age>=89.5 8    3 B2 (0.25 0.62 0 0.12 0) *
##                     417) arthritis>=0.5 99   47 B1 (0.53 0.34 0.071 0.051 0.01)  
##                       834) copd>=0.5 11    2 B1 (0.82 0.091 0.091 0 0) *
##                       835) copd< 0.5 88   45 B1 (0.49 0.38 0.068 0.057 0.011)  
##                        1670) alzheimers< 0.5 63   32 B1 (0.49 0.43 0.063 0 0.016)  
##                          3340) reimbursement2008< 2015 33   14 B1 (0.58 0.3 0.091 0 0.03)  
##                            6680) age>=77.5 19    5 B1 (0.74 0.16 0.11 0 0) *
##                            6681) age< 77.5 14    7 B2 (0.36 0.5 0.071 0 0.071) *
##                          3341) reimbursement2008>=2015 30   13 B2 (0.4 0.57 0.033 0 0)  
##                            6682) osteoporosis>=0.5 12    5 B1 (0.58 0.42 0 0 0) *
##                            6683) osteoporosis< 0.5 18    6 B2 (0.28 0.67 0.056 0 0) *
##                        1671) alzheimers>=0.5 25   13 B1 (0.48 0.24 0.08 0.2 0)  
##                          3342) diabetes< 0.5 10    2 B1 (0.8 0 0.1 0.1 0) *
##                          3343) diabetes>=0.5 15    9 B2 (0.27 0.4 0.067 0.27 0) *
##                   209) age< 73.5 443  228 B1 (0.49 0.32 0.13 0.059 0.009)  
##                     418) heart.failure< 0.5 261  117 B1 (0.55 0.28 0.11 0.057 0.0038)  
##                       836) kidney< 0.5 228   93 B1 (0.59 0.27 0.088 0.048 0.0044)  
##                        1672) age>=43.5 218   85 B1 (0.61 0.26 0.083 0.046 0.0046)  
##                          3344) reimbursement2008< 2485 211   80 B1 (0.62 0.24 0.085 0.047 0.0047)  
##                            6688) diabetes< 0.5 96   29 B1 (0.7 0.2 0.073 0.031 0) *
##                            6689) diabetes>=0.5 115   51 B1 (0.56 0.28 0.096 0.061 0.0087)  
##                             13378) age< 60 20    5 B1 (0.75 0.25 0 0 0) *
##                             13379) age>=60 95   46 B1 (0.52 0.28 0.12 0.074 0.011)  
##                               26758) reimbursement2008< 1735 27    8 B1 (0.7 0.15 0.11 0 0.037) *
##                               26759) reimbursement2008>=1735 68   38 B1 (0.44 0.34 0.12 0.1 0)  
##                                 53518) reimbursement2008>=2145 29   13 B1 (0.55 0.24 0.17 0.034 0)  
##                                  107036) age>=69.5 17    5 B1 (0.71 0.12 0.18 0 0) *
##                                  107037) age< 69.5 12    7 B2 (0.33 0.42 0.17 0.083 0) *
##                                 53519) reimbursement2008< 2145 39   23 B2 (0.36 0.41 0.077 0.15 0)  
##                                  107038) reimbursement2008< 2065 30   17 B1 (0.43 0.37 0.067 0.13 0)  
##                                    214076) reimbursement2008>=1910 12    4 B1 (0.67 0.17 0 0.17 0) *
##                                    214077) reimbursement2008< 1910 18    9 B2 (0.28 0.5 0.11 0.11 0) *
##                                  107039) reimbursement2008>=2065 9    4 B2 (0.11 0.56 0.11 0.22 0) *
##                          3345) reimbursement2008>=2485 7    2 B2 (0.29 0.71 0 0 0) *
##                        1673) age< 43.5 10    5 B2 (0.2 0.5 0.2 0.1 0) *
##                       837) kidney>=0.5 33   21 B2 (0.27 0.36 0.24 0.12 0)  
##                        1674) age< 72.5 26   16 B2 (0.35 0.38 0.12 0.15 0)  
##                          3348) age>=54.5 18   10 B1 (0.44 0.28 0.11 0.17 0) *
##                          3349) age< 54.5 8    3 B2 (0.12 0.62 0.12 0.12 0) *
##                        1675) age>=72.5 7    2 B3 (0 0.29 0.71 0 0) *
##                     419) heart.failure>=0.5 182  111 B1 (0.39 0.37 0.16 0.06 0.016)  
##                       838) copd< 0.5 146   85 B2 (0.38 0.42 0.13 0.055 0.014)  
##                        1676) reimbursement2008< 2235 115   67 B1 (0.42 0.4 0.096 0.07 0.017)  
##                          3352) age>=55.5 98   56 B2 (0.42 0.43 0.061 0.082 0.01)  
##                            6704) reimbursement2008< 2165 88   48 B2 (0.41 0.45 0.068 0.057 0.011)  
##                             13408) reimbursement2008< 1925 55   29 B1 (0.47 0.44 0.036 0.055 0)  
##                               26816) reimbursement2008< 1865 45   23 B2 (0.44 0.49 0.044 0.022 0)  
##                                 53632) age>=66.5 33   16 B1 (0.52 0.42 0.03 0.03 0)  
##                                  107264) reimbursement2008< 1715 18    7 B1 (0.61 0.33 0 0.056 0) *
##                                  107265) reimbursement2008>=1715 15    7 B2 (0.4 0.53 0.067 0 0) *
##                                 53633) age< 66.5 12    4 B2 (0.25 0.67 0.083 0 0) *
##                               26817) reimbursement2008>=1865 10    4 B1 (0.6 0.2 0 0.2 0) *
##                             13409) reimbursement2008>=1925 33   17 B2 (0.3 0.48 0.12 0.061 0.03)  
##                               26818) age>=72.5 7    1 B2 (0.14 0.86 0 0 0) *
##                               26819) age< 72.5 26   16 B2 (0.35 0.38 0.15 0.077 0.038)  
##                                 53638) reimbursement2008>=2005 14    7 B1 (0.5 0.36 0.071 0.071 0) *
##                                 53639) reimbursement2008< 2005 12    7 B2 (0.17 0.42 0.25 0.083 0.083) *
##                            6705) reimbursement2008>=2165 10    5 B1 (0.5 0.2 0 0.3 0) *
##                          3353) age< 55.5 17   10 B1 (0.41 0.24 0.29 0 0.059) *
##                        1677) reimbursement2008>=2235 31   16 B2 (0.26 0.48 0.26 0 0)  
##                          3354) age>=62 23   14 B2 (0.35 0.39 0.26 0 0)  
##                            6708) reimbursement2008>=2305 16    8 B2 (0.31 0.5 0.19 0 0) *
##                            6709) reimbursement2008< 2305 7    4 B1 (0.43 0.14 0.43 0 0) *
##                          3355) age< 62 8    2 B2 (0 0.75 0.25 0 0) *
##                       839) copd>=0.5 36   21 B1 (0.42 0.19 0.28 0.083 0.028)  
##                        1678) age>=69.5 11    5 B1 (0.55 0.36 0.091 0 0) *
##                        1679) age< 69.5 25   16 B1 (0.36 0.12 0.36 0.12 0.04)  
##                          3358) diabetes< 0.5 8    4 B1 (0.5 0.12 0.12 0.25 0) *
##                          3359) diabetes>=0.5 17    9 B3 (0.29 0.12 0.47 0.059 0.059) *
##                 105) stroke>=0.5 31   20 B2 (0.29 0.35 0.32 0.032 0)  
##                   210) age>=75.5 17    8 B2 (0.24 0.53 0.24 0 0) *
##                   211) age< 75.5 14    8 B3 (0.36 0.14 0.43 0.071 0) *
##                53) depression>=0.5 395  225 B1 (0.43 0.38 0.13 0.056 0.0025)  
##                 106) age>=84.5 80   34 B1 (0.57 0.29 0.062 0.075 0)  
##                   212) age< 93.5 55   18 B1 (0.67 0.22 0.055 0.055 0) *
##                   213) age>=93.5 25   14 B2 (0.36 0.44 0.08 0.12 0)  
##                     426) age>=97.5 15    8 B1 (0.47 0.27 0.13 0.13 0) *
##                     427) age< 97.5 10    3 B2 (0.2 0.7 0 0.1 0) *
##                 107) age< 84.5 315  186 B2 (0.39 0.41 0.14 0.051 0.0032)  
##                   214) cancer< 0.5 298  176 B1 (0.41 0.39 0.14 0.05 0.0034)  
##                     428) age< 71.5 162   86 B1 (0.47 0.33 0.12 0.074 0.0062)  
##                       856) reimbursement2008< 1975 76   28 B1 (0.63 0.24 0.053 0.066 0.013)  
##                        1712) copd< 0.5 62   20 B1 (0.68 0.18 0.065 0.065 0.016)  
##                          3424) heart.failure>=0.5 28    6 B1 (0.79 0.036 0.071 0.071 0.036) *
##                          3425) heart.failure< 0.5 34   14 B1 (0.59 0.29 0.059 0.059 0)  
##                            6850) reimbursement2008>=1865 10    2 B1 (0.8 0 0.1 0.1 0) *
##                            6851) reimbursement2008< 1865 24   12 B1 (0.5 0.42 0.042 0.042 0)  
##                             13702) reimbursement2008< 1775 14    4 B1 (0.71 0.29 0 0 0) *
##                             13703) reimbursement2008>=1775 10    4 B2 (0.2 0.6 0.1 0.1 0) *
##                        1713) copd>=0.5 14    7 B2 (0.43 0.5 0 0.071 0) *
##                       857) reimbursement2008>=1975 86   51 B2 (0.33 0.41 0.19 0.081 0)  
##                        1714) alzheimers< 0.5 54   33 B1 (0.39 0.31 0.22 0.074 0)  
##                          3428) reimbursement2008>=2305 25   11 B1 (0.56 0.28 0.12 0.04 0) *
##                          3429) reimbursement2008< 2305 29   19 B2 (0.24 0.34 0.31 0.1 0)  
##                            6858) age>=55 22   12 B2 (0.18 0.45 0.27 0.091 0) *
##                            6859) age< 55 7    4 B1 (0.43 0 0.43 0.14 0) *
##                        1715) alzheimers>=0.5 32   14 B2 (0.22 0.56 0.12 0.094 0) *
##                     429) age>=71.5 136   72 B2 (0.34 0.47 0.17 0.022 0)  
##                       858) reimbursement2008>=1705 117   57 B2 (0.33 0.51 0.15 0.0085 0)  
##                        1716) reimbursement2008>=2445 8    3 B1 (0.62 0.25 0.12 0 0) *
##                        1717) reimbursement2008< 2445 109   51 B2 (0.31 0.53 0.15 0.0092 0)  
##                          3434) reimbursement2008>=2375 10    2 B2 (0.2 0.8 0 0 0) *
##                          3435) reimbursement2008< 2375 99   49 B2 (0.32 0.51 0.16 0.01 0)  
##                            6870) reimbursement2008>=2045 46   27 B1 (0.41 0.41 0.17 0 0)  
##                             13740) copd>=0.5 7    2 B1 (0.71 0 0.29 0 0) *
##                             13741) copd< 0.5 39   20 B2 (0.36 0.49 0.15 0 0)  
##                               27482) heart.failure>=0.5 15    6 B1 (0.6 0.33 0.067 0 0) *
##                               27483) heart.failure< 0.5 24   10 B2 (0.21 0.58 0.21 0 0) *
##                            6871) reimbursement2008< 2045 53   22 B2 (0.25 0.58 0.15 0.019 0)  
##                             13742) reimbursement2008< 1795 13    6 B1 (0.54 0.46 0 0 0) *
##                             13743) reimbursement2008>=1795 40   15 B2 (0.15 0.62 0.2 0.025 0)  
##                               27486) age< 78.5 33   10 B2 (0.12 0.7 0.15 0.03 0) *
##                               27487) age>=78.5 7    4 B3 (0.29 0.29 0.43 0 0) *
##                       859) reimbursement2008< 1705 19   12 B1 (0.37 0.21 0.32 0.11 0) *
##                   215) cancer>=0.5 17    5 B2 (0.12 0.71 0.12 0.059 0) *
##              27) reimbursement2008>=2515 900  539 B2 (0.38 0.4 0.16 0.057 0.0044)  
##                54) arthritis< 0.5 614  349 B1 (0.43 0.35 0.15 0.06 0.0033)  
##                 108) heart.failure< 0.5 317  155 B1 (0.51 0.32 0.13 0.038 0.0063)  
##                   216) cancer< 0.5 281  127 B1 (0.55 0.28 0.12 0.043 0.0071)  
##                     432) age< 67.5 68   24 B1 (0.65 0.26 0.044 0.044 0)  
##                       864) age>=64.5 21    3 B1 (0.86 0.095 0 0.048 0) *
##                       865) age< 64.5 47   21 B1 (0.55 0.34 0.064 0.043 0)  
##                        1730) reimbursement2008>=2765 37   15 B1 (0.59 0.27 0.081 0.054 0) *
##                        1731) reimbursement2008< 2765 10    4 B2 (0.4 0.6 0 0 0) *
##                     433) age>=67.5 213  103 B1 (0.52 0.28 0.15 0.042 0.0094)  
##                       866) diabetes< 0.5 92   35 B1 (0.62 0.23 0.11 0.043 0)  
##                        1732) reimbursement2008>=3170 23    4 B1 (0.83 0.087 0.087 0 0) *
##                        1733) reimbursement2008< 3170 69   31 B1 (0.55 0.28 0.12 0.058 0)  
##                          3466) alzheimers>=0.5 14    3 B1 (0.79 0.14 0 0.071 0) *
##                          3467) alzheimers< 0.5 55   28 B1 (0.49 0.31 0.15 0.055 0)  
##                            6934) age< 83.5 41   23 B1 (0.44 0.41 0.15 0 0)  
##                             13868) reimbursement2008>=2680 30   14 B1 (0.53 0.37 0.1 0 0)  
##                               27736) depression< 0.5 22    8 B1 (0.64 0.32 0.045 0 0) *
##                               27737) depression>=0.5 8    4 B2 (0.25 0.5 0.25 0 0) *
##                             13869) reimbursement2008< 2680 11    5 B2 (0.18 0.55 0.27 0 0) *
##                            6935) age>=83.5 14    5 B1 (0.64 0 0.14 0.21 0) *
##                       867) diabetes>=0.5 121   68 B1 (0.44 0.32 0.18 0.041 0.017)  
##                        1734) age>=69.5 104   54 B1 (0.48 0.28 0.18 0.038 0.019)  
##                          3468) age< 79.5 58   25 B1 (0.57 0.19 0.17 0.034 0.034)  
##                            6936) reimbursement2008>=3325 7    0 B1 (1 0 0 0 0) *
##                            6937) reimbursement2008< 3325 51   25 B1 (0.51 0.22 0.2 0.039 0.039)  
##                             13874) reimbursement2008< 2865 24    9 B1 (0.62 0.12 0.21 0 0.042) *
##                             13875) reimbursement2008>=2865 27   16 B1 (0.41 0.3 0.19 0.074 0.037)  
##                               27750) reimbursement2008>=3040 20   10 B1 (0.5 0.3 0.1 0.1 0)  
##                                 55500) alzheimers>=0.5 8    2 B1 (0.75 0.12 0 0.12 0) *
##                                 55501) alzheimers< 0.5 12    7 B2 (0.33 0.42 0.17 0.083 0) *
##                               27751) reimbursement2008< 3040 7    4 B3 (0.14 0.29 0.43 0 0.14) *
##                          3469) age>=79.5 46   28 B2 (0.37 0.39 0.2 0.043 0)  
##                            6938) kidney< 0.5 33   18 B2 (0.39 0.45 0.12 0.03 0)  
##                             13876) osteoporosis>=0.5 7    2 B2 (0.29 0.71 0 0 0) *
##                             13877) osteoporosis< 0.5 26   15 B1 (0.42 0.38 0.15 0.038 0)  
##                               27754) reimbursement2008< 2785 12    5 B2 (0.33 0.58 0.083 0 0) *
##                               27755) reimbursement2008>=2785 14    7 B1 (0.5 0.21 0.21 0.071 0) *
##                            6939) kidney>=0.5 13    8 B3 (0.31 0.23 0.38 0.077 0) *
##                        1735) age< 69.5 17    7 B2 (0.18 0.59 0.18 0.059 0) *
##                   217) cancer>=0.5 36   14 B2 (0.22 0.61 0.17 0 0)  
##                     434) reimbursement2008< 2770 10    5 B1 (0.5 0.3 0.2 0 0) *
##                     435) reimbursement2008>=2770 26    7 B2 (0.12 0.73 0.15 0 0) *
##                 109) heart.failure>=0.5 297  181 B2 (0.35 0.39 0.18 0.084 0)  
##                   218) kidney< 0.5 213  130 B1 (0.39 0.35 0.15 0.1 0)  
##                     436) alzheimers< 0.5 146   81 B1 (0.45 0.36 0.11 0.089 0)  
##                       872) reimbursement2008>=2585 133   70 B1 (0.47 0.36 0.083 0.083 0)  
##                        1744) reimbursement2008>=3365 8    1 B1 (0.88 0.12 0 0 0) *
##                        1745) reimbursement2008< 3365 125   69 B1 (0.45 0.38 0.088 0.088 0)  
##                          3490) reimbursement2008< 2925 67   31 B1 (0.54 0.27 0.09 0.1 0)  
##                            6980) diabetes< 0.5 23    8 B1 (0.65 0.087 0.13 0.13 0) *
##                            6981) diabetes>=0.5 44   23 B1 (0.48 0.36 0.068 0.091 0)  
##                             13962) reimbursement2008< 2715 23   12 B2 (0.43 0.48 0.043 0.043 0)  
##                               27924) reimbursement2008< 2630 9    3 B1 (0.67 0.22 0 0.11 0) *
##                               27925) reimbursement2008>=2630 14    5 B2 (0.29 0.64 0.071 0 0) *
##                             13963) reimbursement2008>=2715 21   10 B1 (0.52 0.24 0.095 0.14 0)  
##                               27926) age>=71.5 12    4 B1 (0.67 0.083 0.083 0.17 0) *
##                               27927) age< 71.5 9    5 B2 (0.33 0.44 0.11 0.11 0) *
##                          3491) reimbursement2008>=2925 58   29 B2 (0.34 0.5 0.086 0.069 0)  
##                            6982) age< 67.5 13    5 B1 (0.62 0.31 0.077 0 0) *
##                            6983) age>=67.5 45   20 B2 (0.27 0.56 0.089 0.089 0)  
##                             13966) reimbursement2008>=3285 10    5 B1 (0.5 0.3 0.1 0.1 0) *
##                             13967) reimbursement2008< 3285 35   13 B2 (0.2 0.63 0.086 0.086 0) *
##                       873) reimbursement2008< 2585 13    8 B3 (0.15 0.31 0.38 0.15 0) *
##                     437) alzheimers>=0.5 67   44 B2 (0.27 0.34 0.25 0.13 0)  
##                       874) reimbursement2008< 2605 11    6 B1 (0.45 0.18 0.27 0.091 0) *
##                       875) reimbursement2008>=2605 56   35 B2 (0.23 0.38 0.25 0.14 0)  
##                        1750) reimbursement2008< 2755 10    3 B2 (0.1 0.7 0.1 0.1 0) *
##                        1751) reimbursement2008>=2755 46   32 B2 (0.26 0.3 0.28 0.15 0)  
##                          3502) reimbursement2008>=2845 39   27 B1 (0.31 0.31 0.23 0.15 0)  
##                            7004) reimbursement2008>=3120 19   10 B2 (0.21 0.47 0.21 0.11 0) *
##                            7005) reimbursement2008< 3120 20   12 B1 (0.4 0.15 0.25 0.2 0)  
##                             14010) reimbursement2008< 2955 8    3 B1 (0.62 0.25 0.12 0 0) *
##                             14011) reimbursement2008>=2955 12    8 B3 (0.25 0.083 0.33 0.33 0) *
##                          3503) reimbursement2008< 2845 7    3 B3 (0 0.29 0.57 0.14 0) *
##                   219) kidney>=0.5 84   43 B2 (0.24 0.49 0.24 0.036 0)  
##                     438) copd< 0.5 57   28 B2 (0.28 0.51 0.16 0.053 0)  
##                       876) reimbursement2008>=2735 41   16 B2 (0.22 0.61 0.15 0.024 0) *
##                       877) reimbursement2008< 2735 16    9 B1 (0.44 0.25 0.19 0.12 0) *
##                     439) copd>=0.5 27   15 B2 (0.15 0.44 0.41 0 0)  
##                       878) age>=84.5 9    5 B1 (0.44 0.22 0.33 0 0) *
##                       879) age< 84.5 18    8 B2 (0 0.56 0.44 0 0) *
##                55) arthritis>=0.5 286  141 B2 (0.28 0.51 0.16 0.049 0.007)  
##                 110) reimbursement2008< 3015 174   97 B2 (0.31 0.44 0.21 0.034 0.0057)  
##                   220) reimbursement2008< 2965 157   84 B2 (0.32 0.46 0.18 0.032 0.0064)  
##                     440) stroke< 0.5 150   83 B2 (0.33 0.45 0.18 0.033 0.0067)  
##                       880) age< 89.5 142   81 B2 (0.35 0.43 0.19 0.028 0.007)  
##                        1760) kidney< 0.5 104   57 B2 (0.37 0.45 0.13 0.038 0.0096)  
##                          3520) reimbursement2008>=2785 40   22 B1 (0.45 0.38 0.12 0.025 0.025)  
##                            7040) age< 80.5 32   15 B1 (0.53 0.34 0.12 0 0)  
##                             14080) depression< 0.5 18    6 B1 (0.67 0.22 0.11 0 0) *
##                             14081) depression>=0.5 14    7 B2 (0.36 0.5 0.14 0 0) *
##                            7041) age>=80.5 8    4 B2 (0.12 0.5 0.12 0.12 0.12) *
##                          3521) reimbursement2008< 2785 64   32 B2 (0.31 0.5 0.14 0.047 0)  
##                            7042) reimbursement2008>=2565 52   23 B2 (0.29 0.56 0.13 0.019 0) *
##                            7043) reimbursement2008< 2565 12    7 B1 (0.42 0.25 0.17 0.17 0) *
##                        1761) kidney>=0.5 38   24 B2 (0.29 0.37 0.34 0 0)  
##                          3522) alzheimers>=0.5 12    5 B2 (0.33 0.58 0.083 0 0) *
##                          3523) alzheimers< 0.5 26   14 B3 (0.27 0.27 0.46 0 0)  
##                            7046) diabetes>=0.5 19   12 B2 (0.32 0.37 0.32 0 0) *
##                            7047) diabetes< 0.5 7    1 B3 (0.14 0 0.86 0 0) *
##                       881) age>=89.5 8    2 B2 (0.12 0.75 0 0.12 0) *
##                     441) stroke>=0.5 7    1 B2 (0 0.86 0.14 0 0) *
##                   221) reimbursement2008>=2965 17    9 B3 (0.24 0.24 0.47 0.059 0) *
##                 111) reimbursement2008>=3015 112   44 B2 (0.22 0.61 0.089 0.071 0.0089)  
##                   222) kidney< 0.5 81   38 B2 (0.28 0.53 0.099 0.074 0.012)  
##                     444) reimbursement2008>=3075 70   35 B2 (0.31 0.5 0.11 0.057 0.014)  
##                       888) reimbursement2008< 3265 40   23 B1 (0.43 0.4 0.12 0.025 0.025)  
##                        1776) age>=82.5 11    4 B2 (0.27 0.64 0.091 0 0) *
##                        1777) age< 82.5 29   15 B1 (0.48 0.31 0.14 0.034 0.034)  
##                          3554) heart.failure< 0.5 11    2 B1 (0.82 0.18 0 0 0) *
##                          3555) heart.failure>=0.5 18   11 B2 (0.28 0.39 0.22 0.056 0.056) *
##                       889) reimbursement2008>=3265 30   11 B2 (0.17 0.63 0.1 0.1 0) *
##                     445) reimbursement2008< 3075 11    3 B2 (0.091 0.73 0 0.18 0) *
##                   223) kidney>=0.5 31    6 B2 (0.065 0.81 0.065 0.065 0) *
##           7) reimbursement2008>=3425 4596 2775 B2 (0.26 0.4 0.2 0.12 0.017)  
##            14) diabetes< 0.5 1002  558 B1 (0.44 0.33 0.17 0.054 0.003)  
##              28) depression< 0.5 682  335 B1 (0.51 0.3 0.14 0.048 0.0044)  
##                56) cancer< 0.5 563  252 B1 (0.55 0.28 0.13 0.036 0.0053)  
##                 112) arthritis< 0.5 419  169 B1 (0.6 0.26 0.1 0.031 0.0072)  
##                   224) osteoporosis< 0.5 330  125 B1 (0.62 0.23 0.11 0.03 0.0061)  
##                     448) ihd< 0.5 120   33 B1 (0.72 0.17 0.067 0.033 0)  
##                       896) reimbursement2008>=8195 26    2 B1 (0.92 0.038 0.038 0 0) *
##                       897) reimbursement2008< 8195 94   31 B1 (0.67 0.21 0.074 0.043 0)  
##                        1794) heart.failure< 0.5 64   17 B1 (0.73 0.16 0.062 0.047 0) *
##                        1795) heart.failure>=0.5 30   14 B1 (0.53 0.33 0.1 0.033 0)  
##                          3590) copd< 0.5 23    9 B1 (0.61 0.26 0.087 0.043 0) *
##                          3591) copd>=0.5 7    3 B2 (0.29 0.57 0.14 0 0) *
##                     449) ihd>=0.5 210   92 B1 (0.56 0.27 0.13 0.029 0.0095)  
##                       898) reimbursement2008>=7060 89   32 B1 (0.64 0.24 0.079 0.034 0.011)  
##                        1796) reimbursement2008< 9310 22    3 B1 (0.86 0.091 0.045 0 0) *
##                        1797) reimbursement2008>=9310 67   29 B1 (0.57 0.28 0.09 0.045 0.015)  
##                          3594) reimbursement2008>=10695 56   21 B1 (0.62 0.27 0.054 0.036 0.018) *
##                          3595) reimbursement2008< 10695 11    7 B2 (0.27 0.36 0.27 0.091 0) *
##                       899) reimbursement2008< 7060 121   60 B1 (0.5 0.29 0.17 0.025 0.0083)  
##                        1798) reimbursement2008< 6145 105   46 B1 (0.56 0.26 0.16 0.019 0)  
##                          3596) age>=88.5 8    1 B1 (0.88 0.12 0 0 0) *
##                          3597) age< 88.5 97   45 B1 (0.54 0.27 0.18 0.021 0)  
##                            7194) age< 81.5 79   33 B1 (0.58 0.22 0.19 0.013 0)  
##                             14388) reimbursement2008< 4235 32   14 B1 (0.56 0.34 0.062 0.031 0) *
##                             14389) reimbursement2008>=4235 47   19 B1 (0.6 0.13 0.28 0 0)  
##                               28778) age>=70.5 22    6 B1 (0.73 0.091 0.18 0 0) *
##                               28779) age< 70.5 25   13 B1 (0.48 0.16 0.36 0 0)  
##                                 57558) reimbursement2008< 5500 18    7 B1 (0.61 0.11 0.28 0 0) *
##                                 57559) reimbursement2008>=5500 7    3 B3 (0.14 0.29 0.57 0 0) *
##                            7195) age>=81.5 18    9 B2 (0.33 0.5 0.11 0.056 0) *
##                        1799) reimbursement2008>=6145 16    8 B2 (0.12 0.5 0.25 0.062 0.062) *
##                   225) osteoporosis>=0.5 89   44 B1 (0.51 0.38 0.067 0.034 0.011)  
##                     450) reimbursement2008>=12275 15    3 B1 (0.8 0.067 0.067 0.067 0) *
##                     451) reimbursement2008< 12275 74   41 B1 (0.45 0.45 0.068 0.027 0.014)  
##                       902) copd< 0.5 60   30 B1 (0.5 0.38 0.083 0.033 0)  
##                        1804) age< 74.5 26    9 B1 (0.65 0.27 0.077 0 0) *
##                        1805) age>=74.5 34   18 B2 (0.38 0.47 0.088 0.059 0)  
##                          3610) age< 83.5 22    9 B2 (0.32 0.59 0.045 0.045 0) *
##                          3611) age>=83.5 12    6 B1 (0.5 0.25 0.17 0.083 0) *
##                       903) copd>=0.5 14    4 B2 (0.21 0.71 0 0 0.071) *
##                 113) arthritis>=0.5 144   83 B1 (0.42 0.33 0.2 0.049 0)  
##                   226) age< 73.5 58   27 B1 (0.53 0.26 0.14 0.069 0)  
##                     452) reimbursement2008>=6600 27    8 B1 (0.7 0.15 0.037 0.11 0) *
##                     453) reimbursement2008< 6600 31   19 B1 (0.39 0.35 0.23 0.032 0)  
##                       906) heart.failure>=0.5 16    8 B2 (0.31 0.5 0.19 0 0) *
##                       907) heart.failure< 0.5 15    8 B1 (0.47 0.2 0.27 0.067 0) *
##                   227) age>=73.5 86   54 B2 (0.35 0.37 0.24 0.035 0)  
##                     454) ihd< 0.5 14    6 B1 (0.57 0.21 0.14 0.071 0) *
##                     455) ihd>=0.5 72   43 B2 (0.31 0.4 0.26 0.028 0)  
##                       910) reimbursement2008< 4780 18    7 B2 (0.22 0.61 0.17 0 0) *
##                       911) reimbursement2008>=4780 54   36 B1 (0.33 0.33 0.3 0.037 0)  
##                        1822) reimbursement2008>=13120 22   11 B2 (0.32 0.5 0.14 0.045 0)  
##                          3644) reimbursement2008< 14605 7    1 B2 (0.14 0.86 0 0 0) *
##                          3645) reimbursement2008>=14605 15    9 B1 (0.4 0.33 0.2 0.067 0) *
##                        1823) reimbursement2008< 13120 32   19 B3 (0.34 0.22 0.41 0.031 0)  
##                          3646) copd>=0.5 9    5 B1 (0.44 0.33 0.11 0.11 0) *
##                          3647) copd< 0.5 23   11 B3 (0.3 0.17 0.52 0 0) *
##                57) cancer>=0.5 119   75 B2 (0.3 0.37 0.22 0.11 0)  
##                 114) reimbursement2008< 6095 55   34 B1 (0.38 0.27 0.22 0.13 0)  
##                   228) heart.failure< 0.5 42   24 B1 (0.43 0.36 0.095 0.12 0)  
##                     456) reimbursement2008< 3950 10    3 B2 (0.2 0.7 0.1 0 0) *
##                     457) reimbursement2008>=3950 32   16 B1 (0.5 0.25 0.094 0.16 0)  
##                       914) age>=64.5 25   12 B1 (0.52 0.28 0 0.2 0)  
##                        1828) copd< 0.5 18    7 B1 (0.61 0.17 0 0.22 0) *
##                        1829) copd>=0.5 7    3 B2 (0.29 0.57 0 0.14 0) *
##                       915) age< 64.5 7    4 B1 (0.43 0.14 0.43 0 0) *
##                   229) heart.failure>=0.5 13    5 B3 (0.23 0 0.62 0.15 0) *
##                 115) reimbursement2008>=6095 64   35 B2 (0.23 0.45 0.22 0.094 0)  
##                   230) copd< 0.5 41   18 B2 (0.22 0.56 0.12 0.098 0) *
##                   231) copd>=0.5 23   14 B3 (0.26 0.26 0.39 0.087 0)  
##                     462) reimbursement2008>=9740 12    7 B1 (0.42 0.17 0.25 0.17 0) *
##                     463) reimbursement2008< 9740 11    5 B3 (0.091 0.36 0.55 0 0) *
##              29) depression>=0.5 320  190 B2 (0.3 0.41 0.23 0.066 0)  
##                58) copd< 0.5 213  129 B2 (0.35 0.39 0.2 0.056 0)  
##                 116) age< 55.5 20    9 B1 (0.55 0.15 0.3 0 0) *
##                 117) age>=55.5 193  112 B2 (0.33 0.42 0.19 0.062 0)  
##                   234) age< 82.5 136   70 B2 (0.29 0.49 0.17 0.051 0)  
##                     468) heart.failure< 0.5 72   38 B2 (0.39 0.47 0.097 0.042 0)  
##                       936) reimbursement2008>=7260 27   11 B1 (0.59 0.3 0.074 0.037 0)  
##                        1872) reimbursement2008>=14045 11    5 B2 (0.45 0.55 0 0 0) *
##                        1873) reimbursement2008< 14045 16    5 B1 (0.69 0.12 0.12 0.062 0) *
##                       937) reimbursement2008< 7260 45   19 B2 (0.27 0.58 0.11 0.044 0)  
##                        1874) reimbursement2008< 3740 7    3 B1 (0.57 0.29 0.14 0 0) *
##                        1875) reimbursement2008>=3740 38   14 B2 (0.21 0.63 0.11 0.053 0)  
##                          3750) reimbursement2008< 4175 13    2 B2 (0.15 0.85 0 0 0) *
##                          3751) reimbursement2008>=4175 25   12 B2 (0.24 0.52 0.16 0.08 0)  
##                            7502) reimbursement2008< 5090 10    6 B1 (0.4 0.3 0.2 0.1 0) *
##                            7503) reimbursement2008>=5090 15    5 B2 (0.13 0.67 0.13 0.067 0) *
##                     469) heart.failure>=0.5 64   32 B2 (0.19 0.5 0.25 0.062 0)  
##                       938) ihd< 0.5 12    2 B2 (0.083 0.83 0.083 0 0) *
##                       939) ihd>=0.5 52   30 B2 (0.21 0.42 0.29 0.077 0)  
##                        1878) osteoporosis>=0.5 13    4 B2 (0.15 0.69 0.077 0.077 0) *
##                        1879) osteoporosis< 0.5 39   25 B3 (0.23 0.33 0.36 0.077 0)  
##                          3758) reimbursement2008>=5860 25   13 B2 (0.2 0.48 0.24 0.08 0)  
##                            7516) reimbursement2008< 19195 18    8 B2 (0.22 0.56 0.17 0.056 0) *
##                            7517) reimbursement2008>=19195 7    4 B3 (0.14 0.29 0.43 0.14 0) *
##                          3759) reimbursement2008< 5860 14    6 B3 (0.29 0.071 0.57 0.071 0) *
##                   235) age>=82.5 57   33 B1 (0.42 0.26 0.23 0.088 0)  
##                     470) cancer< 0.5 46   24 B1 (0.48 0.2 0.22 0.11 0)  
##                       940) age>=91.5 13    3 B1 (0.77 0.15 0.077 0 0) *
##                       941) age< 91.5 33   21 B1 (0.36 0.21 0.27 0.15 0)  
##                        1882) kidney< 0.5 26   15 B1 (0.42 0.19 0.19 0.19 0) *
##                        1883) kidney>=0.5 7    3 B3 (0.14 0.29 0.57 0 0) *
##                     471) cancer>=0.5 11    5 B2 (0.18 0.55 0.27 0 0) *
##                59) copd>=0.5 107   61 B2 (0.21 0.43 0.28 0.084 0)  
##                 118) reimbursement2008>=25420 13    7 B3 (0.31 0.23 0.46 0 0) *
##                 119) reimbursement2008< 25420 94   51 B2 (0.19 0.46 0.26 0.096 0)  
##                   238) reimbursement2008>=17845 8    1 B2 (0 0.88 0 0.12 0) *
##                   239) reimbursement2008< 17845 86   50 B2 (0.21 0.42 0.28 0.093 0)  
##                     478) reimbursement2008< 15470 79   44 B2 (0.19 0.44 0.29 0.076 0)  
##                       956) age< 75.5 41   25 B2 (0.27 0.39 0.24 0.098 0)  
##                        1912) osteoporosis< 0.5 30   19 B1 (0.37 0.37 0.17 0.1 0)  
##                          3824) age>=68.5 15    7 B1 (0.53 0.27 0.2 0 0) *
##                          3825) age< 68.5 15    8 B2 (0.2 0.47 0.13 0.2 0) *
##                        1913) osteoporosis>=0.5 11    6 B2 (0 0.45 0.45 0.091 0) *
##                       957) age>=75.5 38   19 B2 (0.11 0.5 0.34 0.053 0)  
##                        1914) reimbursement2008>=4300 31   13 B2 (0.097 0.58 0.26 0.065 0) *
##                        1915) reimbursement2008< 4300 7    2 B3 (0.14 0.14 0.71 0 0) *
##                     479) reimbursement2008>=15470 7    4 B1 (0.43 0.14 0.14 0.29 0) *
##            15) diabetes>=0.5 3594 2105 B2 (0.21 0.41 0.21 0.14 0.021)  
##              30) kidney< 0.5 1568  880 B2 (0.29 0.44 0.19 0.075 0.007)  
##                60) arthritis< 0.5 964  571 B2 (0.34 0.41 0.19 0.062 0.0052)  
##                 120) cancer< 0.5 791  473 B2 (0.37 0.4 0.16 0.061 0.0051)  
##                   240) age< 70.5 277  163 B1 (0.41 0.33 0.19 0.069 0.0036)  
##                     480) reimbursement2008< 8845 199  109 B1 (0.45 0.36 0.16 0.025 0)  
##                       960) copd< 0.5 155   78 B1 (0.5 0.3 0.18 0.019 0)  
##                        1920) reimbursement2008>=6290 32   17 B1 (0.47 0.47 0.062 0 0)  
##                          3840) age< 57.5 8    3 B1 (0.62 0.25 0.12 0 0) *
##                          3841) age>=57.5 24   11 B2 (0.42 0.54 0.042 0 0)  
##                            7682) ihd< 0.5 7    3 B1 (0.57 0.43 0 0 0) *
##                            7683) ihd>=0.5 17    7 B2 (0.35 0.59 0.059 0 0) *
##                        1921) reimbursement2008< 6290 123   61 B1 (0.5 0.26 0.21 0.024 0)  
##                          3842) reimbursement2008>=5150 19    4 B1 (0.79 0.053 0.16 0 0) *
##                          3843) reimbursement2008< 5150 104   57 B1 (0.45 0.3 0.22 0.029 0)  
##                            7686) alzheimers< 0.5 76   37 B1 (0.51 0.22 0.24 0.026 0)  
##                             15372) osteoporosis>=0.5 20    6 B1 (0.7 0.15 0.1 0.05 0) *
##                             15373) osteoporosis< 0.5 56   31 B1 (0.45 0.25 0.29 0.018 0)  
##                               30746) reimbursement2008< 3745 17    6 B1 (0.65 0.24 0.12 0 0) *
##                               30747) reimbursement2008>=3745 39   25 B1 (0.36 0.26 0.36 0.026 0)  
##                                 61494) reimbursement2008>=4475 16   10 B1 (0.38 0.38 0.19 0.062 0) *
##                                 61495) reimbursement2008< 4475 23   12 B3 (0.35 0.17 0.48 0 0)  
##                                  122990) age< 59 10    5 B1 (0.5 0.2 0.3 0 0) *
##                                  122991) age>=59 13    5 B3 (0.23 0.15 0.62 0 0) *
##                            7687) alzheimers>=0.5 28   14 B2 (0.29 0.5 0.18 0.036 0) *
##                       961) copd>=0.5 44   19 B2 (0.3 0.57 0.091 0.045 0) *
##                     481) reimbursement2008>=8845 78   54 B1 (0.31 0.24 0.26 0.18 0.013)  
##                       962) reimbursement2008>=11475 52   36 B1 (0.31 0.31 0.17 0.19 0.019)  
##                        1924) copd< 0.5 31   19 B1 (0.39 0.35 0.065 0.16 0.032)  
##                          3848) age>=67.5 7    1 B1 (0.86 0.14 0 0 0) *
##                          3849) age< 67.5 24   14 B2 (0.25 0.42 0.083 0.21 0.042)  
##                            7698) osteoporosis>=0.5 9    5 B1 (0.44 0.22 0 0.22 0.11) *
##                            7699) osteoporosis< 0.5 15    7 B2 (0.13 0.53 0.13 0.2 0) *
##                        1925) copd>=0.5 21   14 B3 (0.19 0.24 0.33 0.24 0)  
##                          3850) age>=56.5 13    7 B3 (0.15 0.23 0.46 0.15 0) *
##                          3851) age< 56.5 8    5 B4 (0.25 0.25 0.12 0.38 0) *
##                       963) reimbursement2008< 11475 26   15 B3 (0.31 0.12 0.42 0.15 0)  
##                        1926) depression< 0.5 15    9 B1 (0.4 0.2 0.33 0.067 0) *
##                        1927) depression>=0.5 11    5 B3 (0.18 0 0.55 0.27 0) *
##                   241) age>=70.5 514  287 B2 (0.35 0.44 0.15 0.056 0.0058)  
##                     482) reimbursement2008>=5045 327  200 B1 (0.39 0.38 0.15 0.067 0.0092)  
##                       964) depression< 0.5 170   92 B1 (0.46 0.34 0.14 0.059 0.0059)  
##                        1928) age< 88.5 144   73 B1 (0.49 0.34 0.1 0.063 0)  
##                          3856) age>=73.5 117   56 B1 (0.52 0.3 0.11 0.068 0)  
##                            7712) reimbursement2008< 5335 11    3 B1 (0.73 0 0.18 0.091 0) *
##                            7713) reimbursement2008>=5335 106   53 B1 (0.5 0.33 0.1 0.066 0)  
##                             15426) reimbursement2008>=6040 85   39 B1 (0.54 0.33 0.12 0.012 0)  
##                               30852) reimbursement2008< 29020 76   32 B1 (0.58 0.32 0.11 0 0)  
##                                 61704) reimbursement2008>=8850 48   16 B1 (0.67 0.23 0.1 0 0) *
##                                 61705) reimbursement2008< 8850 28   15 B2 (0.43 0.46 0.11 0 0)  
##                                  123410) reimbursement2008< 6985 13    4 B1 (0.69 0.15 0.15 0 0) *
##                                  123411) reimbursement2008>=6985 15    4 B2 (0.2 0.73 0.067 0 0) *
##                               30853) reimbursement2008>=29020 9    5 B2 (0.22 0.44 0.22 0.11 0) *
##                             15427) reimbursement2008< 6040 21   14 B1 (0.33 0.33 0.048 0.29 0)  
##                               30854) alzheimers< 0.5 13    7 B1 (0.46 0.31 0.077 0.15 0) *
##                               30855) alzheimers>=0.5 8    4 B4 (0.12 0.38 0 0.5 0) *
##                          3857) age< 73.5 27   13 B2 (0.37 0.52 0.074 0.037 0)  
##                            7714) heart.failure>=0.5 13    6 B1 (0.54 0.38 0.077 0 0) *
##                            7715) heart.failure< 0.5 14    5 B2 (0.21 0.64 0.071 0.071 0) *
##                        1929) age>=88.5 26   17 B2 (0.27 0.35 0.31 0.038 0.038)  
##                          3858) age>=92.5 7    2 B2 (0.14 0.71 0.14 0 0) *
##                          3859) age< 92.5 19   12 B3 (0.32 0.21 0.37 0.053 0.053) *
##                       965) depression>=0.5 157   90 B2 (0.31 0.43 0.17 0.076 0.013)  
##                        1930) age>=88.5 28   13 B1 (0.54 0.32 0.036 0.071 0.036)  
##                          3860) age< 94.5 17    5 B1 (0.71 0.12 0.059 0.12 0) *
##                          3861) age>=94.5 11    4 B2 (0.27 0.64 0 0 0.091) *
##                        1931) age< 88.5 129   71 B2 (0.26 0.45 0.2 0.078 0.0078)  
##                          3862) alzheimers< 0.5 61   26 B2 (0.23 0.57 0.16 0.033 0)  
##                            7724) reimbursement2008>=14285 14    7 B1 (0.5 0.29 0.21 0 0) *
##                            7725) reimbursement2008< 14285 47   16 B2 (0.15 0.66 0.15 0.043 0)  
##                             15450) age< 81.5 26    5 B2 (0.12 0.81 0.077 0 0) *
##                             15451) age>=81.5 21   11 B2 (0.19 0.48 0.24 0.095 0)  
##                               30902) copd< 0.5 10    3 B2 (0.2 0.7 0 0.1 0) *
##                               30903) copd>=0.5 11    6 B3 (0.18 0.27 0.45 0.091 0) *
##                          3863) alzheimers>=0.5 68   45 B2 (0.29 0.34 0.24 0.12 0.015)  
##                            7726) reimbursement2008>=7090 49   30 B2 (0.31 0.39 0.14 0.14 0.02)  
##                             15452) stroke< 0.5 38   23 B1 (0.39 0.34 0.13 0.13 0)  
##                               30904) heart.failure>=0.5 26   13 B1 (0.5 0.27 0.12 0.12 0)  
##                                 61808) osteoporosis< 0.5 18    7 B1 (0.61 0.22 0 0.17 0) *
##                                 61809) osteoporosis>=0.5 8    5 B2 (0.25 0.38 0.38 0 0) *
##                               30905) heart.failure< 0.5 12    6 B2 (0.17 0.5 0.17 0.17 0) *
##                             15453) stroke>=0.5 11    5 B2 (0 0.55 0.18 0.18 0.091) *
##                            7727) reimbursement2008< 7090 19   10 B3 (0.26 0.21 0.47 0.053 0) *
##                     483) reimbursement2008< 5045 187   85 B2 (0.27 0.55 0.14 0.037 0)  
##                       966) age< 77.5 74   26 B2 (0.23 0.65 0.095 0.027 0)  
##                        1932) reimbursement2008< 4725 64   26 B2 (0.27 0.59 0.11 0.031 0)  
##                          3864) reimbursement2008< 4345 50   15 B2 (0.22 0.7 0.04 0.04 0) *
##                          3865) reimbursement2008>=4345 14    8 B1 (0.43 0.21 0.36 0 0) *
##                        1933) reimbursement2008>=4725 10    0 B2 (0 1 0 0 0) *
##                       967) age>=77.5 113   59 B2 (0.3 0.48 0.18 0.044 0)  
##                        1934) age< 78.5 9    3 B1 (0.67 0.11 0.22 0 0) *
##                        1935) age>=78.5 104   51 B2 (0.27 0.51 0.17 0.048 0)  
##                          3870) depression>=0.5 37   23 B1 (0.38 0.38 0.16 0.081 0)  
##                            7740) reimbursement2008< 4035 17    8 B1 (0.53 0.29 0.12 0.059 0) *
##                            7741) reimbursement2008>=4035 20   11 B2 (0.25 0.45 0.2 0.1 0)  
##                             15482) age>=86.5 7    4 B3 (0.29 0.29 0.43 0 0) *
##                             15483) age< 86.5 13    6 B2 (0.23 0.54 0.077 0.15 0) *
##                          3871) depression< 0.5 67   28 B2 (0.21 0.58 0.18 0.03 0) *
##                 121) cancer>=0.5 173   98 B2 (0.18 0.43 0.31 0.069 0.0058)  
##                   242) age>=82.5 39   12 B2 (0.1 0.69 0.15 0.026 0.026) *
##                   243) age< 82.5 134   86 B2 (0.21 0.36 0.35 0.082 0)  
##                     486) age>=55 120   74 B2 (0.21 0.38 0.32 0.092 0)  
##                       972) age< 59.5 8    1 B2 (0.12 0.88 0 0 0) *
##                       973) age>=59.5 112   73 B2 (0.21 0.35 0.34 0.098 0)  
##                        1946) age< 71.5 49   33 B1 (0.33 0.27 0.33 0.082 0)  
##                          3892) copd>=0.5 16    8 B1 (0.5 0.25 0.12 0.12 0) *
##                          3893) copd< 0.5 33   19 B3 (0.24 0.27 0.42 0.061 0)  
##                            7786) reimbursement2008< 5825 11    5 B1 (0.55 0.18 0.27 0 0) *
##                            7787) reimbursement2008>=5825 22   11 B3 (0.091 0.32 0.5 0.091 0)  
##                             15574) heart.failure< 0.5 8    4 B2 (0.12 0.5 0.25 0.12 0) *
##                             15575) heart.failure>=0.5 14    5 B3 (0.071 0.21 0.64 0.071 0) *
##                        1947) age>=71.5 63   37 B2 (0.13 0.41 0.35 0.11 0)  
##                          3894) depression< 0.5 33   19 B3 (0.21 0.27 0.42 0.091 0)  
##                            7788) alzheimers< 0.5 26   17 B2 (0.23 0.35 0.35 0.077 0)  
##                             15576) age>=76.5 16   10 B3 (0.31 0.31 0.38 0 0) *
##                             15577) age< 76.5 10    6 B2 (0.1 0.4 0.3 0.2 0) *
##                            7789) alzheimers>=0.5 7    2 B3 (0.14 0 0.71 0.14 0) *
##                          3895) depression>=0.5 30   13 B2 (0.033 0.57 0.27 0.13 0)  
##                            7790) age< 75.5 13    2 B2 (0 0.85 0.077 0.077 0) *
##                            7791) age>=75.5 17   10 B3 (0.059 0.35 0.41 0.18 0) *
##                     487) age< 55 14    5 B3 (0.21 0.14 0.64 0 0) *
##                61) arthritis>=0.5 604  309 B2 (0.21 0.49 0.2 0.094 0.0099)  
##                 122) reimbursement2008< 3875 69   22 B2 (0.14 0.68 0.13 0.043 0) *
##                 123) reimbursement2008>=3875 535  287 B2 (0.21 0.46 0.21 0.1 0.011)  
##                   246) depression< 0.5 282  149 B2 (0.24 0.47 0.16 0.12 0.014)  
##                     492) alzheimers< 0.5 183  102 B2 (0.28 0.44 0.13 0.13 0.022)  
##                       984) reimbursement2008>=11200 56   35 B1 (0.38 0.36 0.11 0.11 0.054)  
##                        1968) copd< 0.5 38   19 B1 (0.5 0.32 0.053 0.11 0.026)  
##                          3936) age>=67.5 30   13 B1 (0.57 0.33 0.033 0.033 0.033) *
##                          3937) age< 67.5 8    5 B4 (0.25 0.25 0.12 0.38 0) *
##                        1969) copd>=0.5 18   10 B2 (0.11 0.44 0.22 0.11 0.11) *
##                       985) reimbursement2008< 11200 127   66 B2 (0.24 0.48 0.13 0.13 0.0079)  
##                        1970) reimbursement2008< 6240 85   47 B2 (0.32 0.45 0.13 0.094 0.012)  
##                          3940) age< 80.5 59   29 B2 (0.32 0.51 0.1 0.051 0.017)  
##                            7880) reimbursement2008< 4180 7    2 B1 (0.71 0.14 0.14 0 0) *
##                            7881) reimbursement2008>=4180 52   23 B2 (0.27 0.56 0.096 0.058 0.019)  
##                             15762) reimbursement2008>=4955 32   18 B2 (0.38 0.44 0.094 0.062 0.031)  
##                               31524) ihd< 0.5 8    2 B1 (0.75 0.25 0 0 0) *
##                               31525) ihd>=0.5 24   12 B2 (0.25 0.5 0.12 0.083 0.042) *
##                             15763) reimbursement2008< 4955 20    5 B2 (0.1 0.75 0.1 0.05 0) *
##                          3941) age>=80.5 26   18 B1 (0.31 0.31 0.19 0.19 0)  
##                            7882) osteoporosis< 0.5 18   10 B1 (0.44 0.28 0.17 0.11 0) *
##                            7883) osteoporosis>=0.5 8    5 B2 (0 0.38 0.25 0.38 0) *
##                        1971) reimbursement2008>=6240 42   19 B2 (0.095 0.55 0.14 0.21 0)  
##                          3942) age>=67.5 32   11 B2 (0.031 0.66 0.12 0.19 0) *
##                          3943) age< 67.5 10    7 B1 (0.3 0.2 0.2 0.3 0) *
##                     493) alzheimers>=0.5 99   47 B2 (0.16 0.53 0.21 0.1 0)  
##                       986) age>=79.5 37   22 B2 (0.27 0.41 0.14 0.19 0)  
##                        1972) heart.failure< 0.5 16   10 B1 (0.38 0.38 0.25 0 0) *
##                        1973) heart.failure>=0.5 21   12 B2 (0.19 0.43 0.048 0.33 0)  
##                          3946) age>=87 10    4 B2 (0.2 0.6 0 0.2 0) *
##                          3947) age< 87 11    6 B4 (0.18 0.27 0.091 0.45 0) *
##                       987) age< 79.5 62   25 B2 (0.097 0.6 0.26 0.048 0)  
##                        1974) reimbursement2008>=9010 17    4 B2 (0.059 0.76 0.12 0.059 0) *
##                        1975) reimbursement2008< 9010 45   21 B2 (0.11 0.53 0.31 0.044 0)  
##                          3950) reimbursement2008< 5595 23    7 B2 (0.087 0.7 0.13 0.087 0) *
##                          3951) reimbursement2008>=5595 22   11 B3 (0.14 0.36 0.5 0 0)  
##                            7902) reimbursement2008>=6650 15    8 B2 (0.2 0.47 0.33 0 0) *
##                            7903) reimbursement2008< 6650 7    1 B3 (0 0.14 0.86 0 0) *
##                   247) depression>=0.5 253  138 B2 (0.18 0.45 0.27 0.083 0.0079)  
##                     494) age>=40.5 241  131 B2 (0.19 0.46 0.26 0.087 0.0083)  
##                       988) age< 54.5 16    5 B2 (0.19 0.69 0.12 0 0) *
##                       989) age>=54.5 225  126 B2 (0.19 0.44 0.27 0.093 0.0089)  
##                        1978) reimbursement2008< 39120 216  118 B2 (0.19 0.45 0.26 0.083 0.0093)  
##                          3956) reimbursement2008>=15105 52   22 B2 (0.15 0.58 0.19 0.077 0)  
##                            7912) reimbursement2008< 23850 30    8 B2 (0.1 0.73 0.067 0.1 0) *
##                            7913) reimbursement2008>=23850 22   14 B2 (0.23 0.36 0.36 0.045 0)  
##                             15826) age>=72.5 12    5 B2 (0.17 0.58 0.25 0 0) *
##                             15827) age< 72.5 10    5 B3 (0.3 0.1 0.5 0.1 0) *
##                          3957) reimbursement2008< 15105 164   96 B2 (0.21 0.41 0.28 0.085 0.012)  
##                            7914) alzheimers< 0.5 90   47 B2 (0.2 0.48 0.22 0.089 0.011)  
##                             15828) osteoporosis< 0.5 53   28 B2 (0.26 0.47 0.13 0.11 0.019)  
##                               31656) copd>=0.5 10    5 B1 (0.5 0.2 0.1 0.1 0.1) *
##                               31657) copd< 0.5 43   20 B2 (0.21 0.53 0.14 0.12 0)  
##                                 63314) reimbursement2008>=4140 36   15 B2 (0.22 0.58 0.14 0.056 0)  
##                                  126628) reimbursement2008< 5440 13    2 B2 (0.077 0.85 0.077 0 0) *
##                                  126629) reimbursement2008>=5440 23   13 B2 (0.3 0.43 0.17 0.087 0)  
##                                    253258) reimbursement2008< 5980 7    3 B1 (0.57 0.29 0 0.14 0) *
##                                    253259) reimbursement2008>=5980 16    8 B2 (0.19 0.5 0.25 0.062 0) *
##                                 63315) reimbursement2008< 4140 7    4 B4 (0.14 0.29 0.14 0.43 0) *
##                             15829) osteoporosis>=0.5 37   19 B2 (0.11 0.49 0.35 0.054 0)  
##                               31658) age>=74.5 15    4 B2 (0 0.73 0.2 0.067 0) *
##                               31659) age< 74.5 22   12 B3 (0.18 0.32 0.45 0.045 0) *
##                            7915) alzheimers>=0.5 74   48 B3 (0.22 0.34 0.35 0.081 0.014)  
##                             15830) age< 79.5 46   27 B2 (0.15 0.41 0.39 0.043 0)  
##                               31660) reimbursement2008< 5620 10    3 B2 (0.1 0.7 0.2 0 0) *
##                               31661) reimbursement2008>=5620 36   20 B3 (0.17 0.33 0.44 0.056 0)  
##                                 63322) reimbursement2008>=8035 21   11 B2 (0.19 0.48 0.24 0.095 0)  
##                                  126644) age< 67.5 9    6 B1 (0.33 0.22 0.33 0.11 0) *
##                                  126645) age>=67.5 12    4 B2 (0.083 0.67 0.17 0.083 0) *
##                                 63323) reimbursement2008< 8035 15    4 B3 (0.13 0.13 0.73 0 0) *
##                             15831) age>=79.5 28   19 B1 (0.32 0.21 0.29 0.14 0.036)  
##                               31662) age< 84.5 9    3 B1 (0.67 0 0.11 0.11 0.11) *
##                               31663) age>=84.5 19   12 B3 (0.16 0.32 0.37 0.16 0) *
##                        1979) reimbursement2008>=39120 9    5 B3 (0.11 0.11 0.44 0.33 0) *
##                     495) age< 40.5 12    5 B3 (0 0.42 0.58 0 0) *
##              31) kidney>=0.5 2026 1225 B2 (0.15 0.4 0.23 0.19 0.033)  
##                62) reimbursement2008< 15095 1090  627 B2 (0.18 0.42 0.24 0.14 0.021)  
##                 124) arthritis< 0.5 638  402 B2 (0.22 0.37 0.24 0.15 0.025)  
##                   248) age>=44.5 612  383 B2 (0.23 0.37 0.23 0.15 0.026)  
##                     496) reimbursement2008>=6575 346  226 B2 (0.25 0.35 0.21 0.16 0.029)  
##                       992) age>=85.5 67   45 B1 (0.33 0.27 0.31 0.06 0.03)  
##                        1984) osteoporosis< 0.5 43   25 B1 (0.42 0.21 0.28 0.047 0.047)  
##                          3968) reimbursement2008< 8495 11    3 B1 (0.73 0 0.27 0 0) *
##                          3969) reimbursement2008>=8495 32   22 B1 (0.31 0.28 0.28 0.062 0.062)  
##                            7938) age< 96.5 24   15 B3 (0.29 0.33 0.38 0 0)  
##                             15876) reimbursement2008>=13055 13    7 B1 (0.46 0.23 0.31 0 0) *
##                             15877) reimbursement2008< 13055 11    6 B2 (0.091 0.45 0.45 0 0) *
##                            7939) age>=96.5 8    5 B1 (0.38 0.12 0 0.25 0.25) *
##                        1985) osteoporosis>=0.5 24   15 B2 (0.17 0.38 0.38 0.083 0)  
##                          3970) reimbursement2008< 9045 8    2 B2 (0 0.75 0.25 0 0) *
##                          3971) reimbursement2008>=9045 16    9 B3 (0.25 0.19 0.44 0.12 0) *
##                       993) age< 85.5 279  177 B2 (0.24 0.37 0.18 0.19 0.029)  
##                        1986) reimbursement2008< 6780 11    5 B1 (0.55 0.091 0.091 0.27 0) *
##                        1987) reimbursement2008>=6780 268  167 B2 (0.22 0.38 0.18 0.19 0.03)  
##                          3974) age< 77.5 177  108 B2 (0.26 0.39 0.14 0.18 0.028)  
##                            7948) reimbursement2008< 14365 169  100 B2 (0.25 0.41 0.12 0.18 0.03)  
##                             15896) age>=75.5 24   13 B1 (0.46 0.25 0.042 0.21 0.042)  
##                               31792) copd< 0.5 10    3 B1 (0.7 0 0.1 0.1 0.1) *
##                               31793) copd>=0.5 14    8 B2 (0.29 0.43 0 0.29 0) *
##                             15897) age< 75.5 145   82 B2 (0.22 0.43 0.14 0.18 0.028)  
##                               31794) stroke>=0.5 18    7 B2 (0.11 0.61 0.22 0.056 0) *
##                               31795) stroke< 0.5 127   75 B2 (0.24 0.41 0.13 0.2 0.031)  
##                                 63590) age>=68.5 65   34 B2 (0.25 0.48 0.15 0.11 0.015)  
##                                  127180) reimbursement2008< 10335 39   25 B1 (0.36 0.36 0.18 0.1 0)  
##                                    254360) reimbursement2008>=9355 8    3 B1 (0.62 0 0.12 0.25 0) *
##                                    254361) reimbursement2008< 9355 31   17 B2 (0.29 0.45 0.19 0.065 0)  
##                                      508722) heart.failure< 0.5 9    4 B1 (0.56 0.22 0.22 0 0) *
##                                      508723) heart.failure>=0.5 22   10 B2 (0.18 0.55 0.18 0.091 0)  
##                                       1017446) age< 71.5 12    3 B2 (0.17 0.75 0 0.083 0) *
##                                       1017447) age>=71.5 10    6 B3 (0.2 0.3 0.4 0.1 0) *
##                                  127181) reimbursement2008>=10335 26    9 B2 (0.077 0.65 0.12 0.12 0.038) *
##                                 63591) age< 68.5 62   41 B2 (0.23 0.34 0.097 0.29 0.048)  
##                                  127182) reimbursement2008>=10290 28   18 B4 (0.32 0.21 0.071 0.36 0.036)  
##                                    254364) reimbursement2008< 10940 7    3 B1 (0.57 0 0.29 0.14 0) *
##                                    254365) reimbursement2008>=10940 21   12 B4 (0.24 0.29 0 0.43 0.048)  
##                                      508730) alzheimers< 0.5 13    8 B2 (0.23 0.38 0 0.31 0.077) *
##                                      508731) alzheimers>=0.5 8    3 B4 (0.25 0.12 0 0.62 0) *
##                                  127183) reimbursement2008< 10290 34   19 B2 (0.15 0.44 0.12 0.24 0.059)  
##                                    254366) age< 65.5 25   12 B2 (0.16 0.52 0.12 0.12 0.08) *
##                                    254367) age>=65.5 9    4 B4 (0.11 0.22 0.11 0.56 0) *
##                            7949) reimbursement2008>=14365 8    4 B3 (0.38 0 0.5 0.12 0) *
##                          3975) age>=77.5 91   59 B2 (0.15 0.35 0.26 0.2 0.033)  
##                            7950) alzheimers< 0.5 34   23 B3 (0.26 0.24 0.32 0.12 0.059)  
##                             15900) copd>=0.5 10    5 B2 (0.2 0.5 0.2 0 0.1) *
##                             15901) copd< 0.5 24   15 B3 (0.29 0.12 0.38 0.17 0.042)  
##                               31802) cancer< 0.5 17   10 B1 (0.41 0.12 0.29 0.12 0.059) *
##                               31803) cancer>=0.5 7    3 B3 (0 0.14 0.57 0.29 0) *
##                            7951) alzheimers>=0.5 57   33 B2 (0.088 0.42 0.23 0.25 0.018)  
##                             15902) reimbursement2008>=9695 38   18 B2 (0.079 0.53 0.26 0.13 0)  
##                               31804) reimbursement2008< 13070 23   10 B2 (0.087 0.57 0.35 0 0)  
##                                 63608) reimbursement2008< 11420 13    4 B2 (0.077 0.69 0.23 0 0) *
##                                 63609) reimbursement2008>=11420 10    5 B3 (0.1 0.4 0.5 0 0) *
##                               31805) reimbursement2008>=13070 15    8 B2 (0.067 0.47 0.13 0.33 0) *
##                             15903) reimbursement2008< 9695 19   10 B4 (0.11 0.21 0.16 0.47 0.053) *
##                     497) reimbursement2008< 6575 266  157 B2 (0.19 0.41 0.26 0.12 0.023)  
##                       994) age>=92.5 19    5 B2 (0.16 0.74 0.053 0.053 0) *
##                       995) age< 92.5 247  152 B2 (0.19 0.38 0.27 0.13 0.024)  
##                        1990) age< 88.5 235  142 B2 (0.19 0.4 0.25 0.14 0.026)  
##                          3980) reimbursement2008< 6170 210  127 B2 (0.21 0.4 0.22 0.15 0.024)  
##                            7960) age>=81.5 48   23 B2 (0.19 0.52 0.15 0.12 0.021)  
##                             15920) depression< 0.5 25   15 B2 (0.32 0.4 0.12 0.12 0.04)  
##                               31840) alzheimers>=0.5 12    5 B1 (0.58 0.17 0.083 0.17 0) *
##                               31841) alzheimers< 0.5 13    5 B2 (0.077 0.62 0.15 0.077 0.077) *
##                             15921) depression>=0.5 23    8 B2 (0.043 0.65 0.17 0.13 0) *
##                            7961) age< 81.5 162  104 B2 (0.22 0.36 0.25 0.15 0.025)  
##                             15922) reimbursement2008< 4895 94   54 B2 (0.23 0.43 0.18 0.14 0.021)  
##                               31844) reimbursement2008< 4080 47   32 B1 (0.32 0.3 0.21 0.13 0.043)  
##                                 63688) age< 60.5 7    2 B2 (0.14 0.71 0.14 0 0) *
##                                 63689) age>=60.5 40   26 B1 (0.35 0.23 0.23 0.15 0.05)  
##                                  127378) age< 71.5 14    6 B1 (0.57 0.21 0.071 0.14 0) *
##                                  127379) age>=71.5 26   18 B3 (0.23 0.23 0.31 0.15 0.077)  
##                                    254758) reimbursement2008< 3885 19   13 B1 (0.32 0.21 0.21 0.16 0.11) *
##                                    254759) reimbursement2008>=3885 7    3 B3 (0 0.29 0.57 0.14 0) *
##                               31845) reimbursement2008>=4080 47   21 B2 (0.15 0.55 0.15 0.15 0) *
##                             15923) reimbursement2008>=4895 68   45 B3 (0.19 0.26 0.34 0.18 0.029)  
##                               31846) alzheimers< 0.5 39   27 B2 (0.28 0.31 0.23 0.15 0.026)  
##                                 63692) age>=76.5 15    9 B3 (0.27 0.33 0.4 0 0) *
##                                 63693) age< 76.5 24   17 B1 (0.29 0.29 0.12 0.25 0.042)  
##                                  127386) depression>=0.5 14    8 B2 (0.36 0.43 0.071 0.071 0.071) *
##                                  127387) depression< 0.5 10    5 B4 (0.2 0.1 0.2 0.5 0) *
##                               31847) alzheimers>=0.5 29   15 B3 (0.069 0.21 0.48 0.21 0.034) *
##                          3981) reimbursement2008>=6170 25   13 B3 (0.04 0.4 0.48 0.04 0.04)  
##                            7962) reimbursement2008>=6260 17    8 B2 (0 0.53 0.41 0 0.059) *
##                            7963) reimbursement2008< 6260 8    3 B3 (0.12 0.12 0.62 0.12 0) *
##                        1991) age>=88.5 12    4 B3 (0.17 0.17 0.67 0 0) *
##                   249) age< 44.5 26   11 B3 (0.038 0.27 0.58 0.12 0)  
##                     498) age< 34 7    3 B2 (0 0.57 0.43 0 0) *
##                     499) age>=34 19    7 B3 (0.053 0.16 0.63 0.16 0) *
##                 125) arthritis>=0.5 452  225 B2 (0.12 0.5 0.24 0.12 0.015)  
##                   250) reimbursement2008< 5300 143   58 B2 (0.14 0.59 0.15 0.1 0.007)  
##                     500) reimbursement2008>=5155 11    1 B2 (0 0.91 0 0.091 0) *
##                     501) reimbursement2008< 5155 132   57 B2 (0.15 0.57 0.17 0.11 0.0076)  
##                      1002) reimbursement2008< 4815 107   42 B2 (0.15 0.61 0.14 0.093 0.0093)  
##                        2004) reimbursement2008< 4595 88   38 B2 (0.18 0.57 0.16 0.08 0.011)  
##                          4008) reimbursement2008< 3725 19    5 B2 (0.11 0.74 0.053 0.11 0) *
##                          4009) reimbursement2008>=3725 69   33 B2 (0.2 0.52 0.19 0.072 0.014)  
##                            8018) osteoporosis>=0.5 29   15 B2 (0.34 0.48 0.1 0.069 0)  
##                             16036) reimbursement2008< 4270 22   10 B2 (0.41 0.55 0.045 0 0)  
##                               32072) reimbursement2008< 3905 7    3 B1 (0.57 0.29 0.14 0 0) *
##                               32073) reimbursement2008>=3905 15    5 B2 (0.33 0.67 0 0 0) *
##                             16037) reimbursement2008>=4270 7    5 B2 (0.14 0.29 0.29 0.29 0) *
##                            8019) osteoporosis< 0.5 40   18 B2 (0.1 0.55 0.25 0.075 0.025)  
##                             16038) reimbursement2008>=3995 31   11 B2 (0.097 0.65 0.16 0.065 0.032) *
##                             16039) reimbursement2008< 3995 9    4 B3 (0.11 0.22 0.56 0.11 0) *
##                        2005) reimbursement2008>=4595 19    4 B2 (0 0.79 0.053 0.16 0) *
##                      1003) reimbursement2008>=4815 25   15 B2 (0.16 0.4 0.28 0.16 0)  
##                        2006) reimbursement2008>=4975 16    8 B2 (0.19 0.5 0.19 0.12 0) *
##                        2007) reimbursement2008< 4975 9    5 B3 (0.11 0.22 0.44 0.22 0) *
##                   251) reimbursement2008>=5300 309  167 B2 (0.12 0.46 0.28 0.13 0.019)  
##                     502) ihd< 0.5 24   16 B3 (0.29 0.29 0.33 0.083 0)  
##                      1004) age>=70 16   10 B1 (0.38 0.31 0.19 0.12 0) *
##                      1005) age< 70 8    3 B3 (0.12 0.25 0.62 0 0) *
##                     503) ihd>=0.5 285  150 B2 (0.1 0.47 0.27 0.13 0.021)  
##                      1006) reimbursement2008>=5725 253  138 B2 (0.11 0.45 0.27 0.14 0.02)  
##                        2012) reimbursement2008< 6565 35   23 B3 (0.2 0.31 0.34 0.14 0)  
##                          4024) age< 72.5 13    7 B2 (0.23 0.46 0.15 0.15 0) *
##                          4025) age>=72.5 22   12 B3 (0.18 0.23 0.45 0.14 0) *
##                        2013) reimbursement2008>=6565 218  114 B2 (0.1 0.48 0.26 0.14 0.023)  
##                          4026) reimbursement2008>=7265 187  100 B2 (0.11 0.47 0.28 0.12 0.027)  
##                            8052) heart.failure< 0.5 35   21 B2 (0.2 0.4 0.2 0.17 0.029) *
##                            8053) heart.failure>=0.5 152   79 B2 (0.086 0.48 0.3 0.11 0.026)  
##                             16106) reimbursement2008< 13595 130   65 B2 (0.1 0.5 0.28 0.11 0.015)  
##                               32212) reimbursement2008>=10630 52   24 B2 (0.15 0.54 0.19 0.096 0.019)  
##                                 64424) reimbursement2008< 11260 14    2 B2 (0.071 0.86 0.071 0 0) *
##                                 64425) reimbursement2008>=11260 38   22 B2 (0.18 0.42 0.24 0.13 0.026)  
##                                  128850) alzheimers>=0.5 25   12 B2 (0.2 0.52 0.12 0.12 0.04) *
##                                  128851) alzheimers< 0.5 13    7 B3 (0.15 0.23 0.46 0.15 0) *
##                               32213) reimbursement2008< 10630 78   41 B2 (0.064 0.47 0.33 0.12 0.013)  
##                                 64426) depression< 0.5 37   17 B2 (0.081 0.54 0.27 0.11 0) *
##                                 64427) depression>=0.5 41   24 B2 (0.049 0.41 0.39 0.12 0.024)  
##                                  128854) reimbursement2008< 10175 34   18 B2 (0.029 0.47 0.35 0.12 0.029)  
##                                    257708) reimbursement2008>=9480 7    2 B2 (0 0.71 0.14 0.14 0) *
##                                    257709) reimbursement2008< 9480 27   16 B2 (0.037 0.41 0.41 0.11 0.037)  
##                                      515418) reimbursement2008< 9020 19   10 B2 (0.053 0.47 0.26 0.16 0.053) *
##                                      515419) reimbursement2008>=9020 8    2 B3 (0 0.25 0.75 0 0) *
##                                  128855) reimbursement2008>=10175 7    3 B3 (0.14 0.14 0.57 0.14 0) *
##                             16107) reimbursement2008>=13595 22   12 B3 (0 0.36 0.45 0.091 0.091)  
##                               32214) reimbursement2008>=14005 14    7 B2 (0 0.5 0.36 0 0.14) *
##                               32215) reimbursement2008< 14005 8    3 B3 (0 0.12 0.62 0.25 0) *
##                          4027) reimbursement2008< 7265 31   14 B2 (0.065 0.55 0.13 0.26 0) *
##                      1007) reimbursement2008< 5725 32   12 B2 (0 0.62 0.25 0.094 0.031)  
##                        2014) reimbursement2008>=5385 22    5 B2 (0 0.77 0.18 0 0.045) *
##                        2015) reimbursement2008< 5385 10    6 B3 (0 0.3 0.4 0.3 0) *
##                63) reimbursement2008>=15095 936  598 B2 (0.13 0.36 0.22 0.24 0.046)  
##                 126) ihd< 0.5 53   35 B2 (0.3 0.34 0.075 0.26 0.019)  
##                   252) reimbursement2008>=25800 20    9 B1 (0.55 0.25 0.05 0.15 0)  
##                     504) age< 79.5 11    2 B1 (0.82 0 0.091 0.091 0) *
##                     505) age>=79.5 9    4 B2 (0.22 0.56 0 0.22 0) *
##                   253) reimbursement2008< 25800 33   20 B2 (0.15 0.39 0.091 0.33 0.03)  
##                     506) age< 79.5 20    8 B2 (0.05 0.6 0.1 0.2 0.05)  
##                      1012) reimbursement2008< 22825 13    2 B2 (0.077 0.85 0 0 0.077) *
##                      1013) reimbursement2008>=22825 7    3 B4 (0 0.14 0.29 0.57 0) *
##                     507) age>=79.5 13    6 B4 (0.31 0.077 0.077 0.54 0) *
##                 127) ihd>=0.5 883  563 B2 (0.12 0.36 0.23 0.24 0.048)  
##                   254) reimbursement2008< 26375 396  261 B2 (0.17 0.34 0.25 0.2 0.043)  
##                     508) arthritis< 0.5 233  160 B2 (0.21 0.31 0.21 0.24 0.034)  
##                      1016) copd< 0.5 95   68 B1 (0.28 0.24 0.21 0.26 0)  
##                        2032) reimbursement2008>=18065 67   45 B1 (0.33 0.18 0.25 0.24 0)  
##                          4064) reimbursement2008>=18390 59   39 B1 (0.34 0.2 0.2 0.25 0)  
##                            8128) stroke>=0.5 10    5 B2 (0.4 0.5 0.1 0 0) *
##                            8129) stroke< 0.5 49   33 B1 (0.33 0.14 0.22 0.31 0)  
##                             16258) age< 86.5 41   26 B1 (0.37 0.17 0.22 0.24 0)  
##                               32516) depression>=0.5 23   11 B1 (0.52 0.087 0.13 0.26 0) *
##                               32517) depression< 0.5 18   12 B3 (0.17 0.28 0.33 0.22 0) *
##                             16259) age>=86.5 8    3 B4 (0.12 0 0.25 0.62 0) *
##                          4065) reimbursement2008< 18390 8    3 B3 (0.25 0 0.62 0.12 0) *
##                        2033) reimbursement2008< 18065 28   17 B2 (0.18 0.39 0.11 0.32 0)  
##                          4066) reimbursement2008< 16540 9    6 B1 (0.33 0.11 0.33 0.22 0) *
##                          4067) reimbursement2008>=16540 19    9 B2 (0.11 0.53 0 0.37 0) *
##                      1017) copd>=0.5 138   88 B2 (0.15 0.36 0.21 0.22 0.058)  
##                        2034) reimbursement2008>=22770 41   21 B2 (0.17 0.49 0.15 0.098 0.098)  
##                          4068) age< 83.5 32   13 B2 (0.12 0.59 0.12 0.094 0.062)  
##                            8136) reimbursement2008>=25510 7    4 B1 (0.43 0.14 0.14 0.29 0) *
##                            8137) reimbursement2008< 25510 25    7 B2 (0.04 0.72 0.12 0.04 0.08) *
##                          4069) age>=83.5 9    6 B1 (0.33 0.11 0.22 0.11 0.22) *
##                        2035) reimbursement2008< 22770 97   67 B2 (0.14 0.31 0.24 0.27 0.041)  
##                          4070) reimbursement2008< 21150 81   53 B2 (0.17 0.35 0.22 0.22 0.037)  
##                            8140) age< 73.5 35   18 B2 (0.14 0.49 0.17 0.14 0.057)  
##                             16280) age>=60 28   12 B2 (0.18 0.57 0.11 0.11 0.036) *
##                             16281) age< 60 7    4 B3 (0 0.14 0.43 0.29 0.14) *
##                            8141) age>=73.5 46   33 B4 (0.2 0.24 0.26 0.28 0.022)  
##                             16282) age>=75.5 39   28 B2 (0.23 0.28 0.23 0.23 0.026)  
##                               32564) age< 80 10    5 B3 (0.2 0.3 0.5 0 0) *
##                               32565) age>=80 29   20 B4 (0.24 0.28 0.14 0.31 0.034)  
##                                 65130) age>=83.5 22   14 B2 (0.27 0.36 0.14 0.23 0)  
##                                  130260) reimbursement2008>=17685 10    6 B1 (0.4 0.3 0.2 0.1 0) *
##                                  130261) reimbursement2008< 17685 12    7 B2 (0.17 0.42 0.083 0.33 0) *
##                                 65131) age< 83.5 7    3 B4 (0.14 0 0.14 0.57 0.14) *
##                             16283) age< 75.5 7    3 B4 (0 0 0.43 0.57 0) *
##                          4071) reimbursement2008>=21150 16    8 B4 (0 0.12 0.31 0.5 0.062) *
##                     509) arthritis>=0.5 163  101 B2 (0.11 0.38 0.31 0.15 0.055)  
##                      1018) heart.failure>=0.5 140   83 B2 (0.12 0.41 0.27 0.14 0.057)  
##                        2036) age>=65 125   71 B2 (0.14 0.43 0.26 0.13 0.048)  
##                          4072) reimbursement2008>=22510 36   19 B2 (0.11 0.47 0.36 0 0.056)  
##                            8144) reimbursement2008>=22930 29   13 B2 (0.1 0.55 0.31 0 0.034)  
##                             16288) age< 86 22    8 B2 (0.091 0.64 0.27 0 0) *
##                             16289) age>=86 7    4 B3 (0.14 0.29 0.43 0 0.14) *
##                            8145) reimbursement2008< 22930 7    3 B3 (0.14 0.14 0.57 0 0.14) *
##                          4073) reimbursement2008< 22510 89   52 B2 (0.15 0.42 0.21 0.18 0.045)  
##                            8146) reimbursement2008>=17640 55   33 B2 (0.24 0.4 0.16 0.16 0.036)  
##                             16292) reimbursement2008< 18970 20   11 B1 (0.45 0.2 0.2 0.15 0)  
##                               32584) depression>=0.5 10    6 B2 (0.3 0.4 0.3 0 0) *
##                               32585) depression< 0.5 10    4 B1 (0.6 0 0.1 0.3 0) *
##                             16293) reimbursement2008>=18970 35   17 B2 (0.11 0.51 0.14 0.17 0.057) *
##                            8147) reimbursement2008< 17640 34   19 B2 (0 0.44 0.29 0.21 0.059)  
##                             16294) age< 77 9    2 B2 (0 0.78 0.22 0 0) *
##                             16295) age>=77 25   17 B2 (0 0.32 0.32 0.28 0.08)  
##                               32590) age< 82.5 10    5 B3 (0 0.3 0.5 0.1 0.1) *
##                               32591) age>=82.5 15    9 B4 (0 0.33 0.2 0.4 0.067) *
##                        2037) age< 65 15    9 B3 (0 0.2 0.4 0.27 0.13) *
##                      1019) heart.failure< 0.5 23   11 B3 (0.043 0.22 0.52 0.17 0.043)  
##                        2038) copd< 0.5 13    8 B2 (0.077 0.38 0.23 0.23 0.077) *
##                        2039) copd>=0.5 10    1 B3 (0 0 0.9 0.1 0) *
##                   255) reimbursement2008>=26375 487  302 B2 (0.076 0.38 0.21 0.28 0.051)  
##                     510) age>=88.5 65   28 B2 (0.11 0.57 0.11 0.15 0.062) *
##                     511) age< 88.5 422  274 B2 (0.071 0.35 0.23 0.3 0.05)  
##                      1022) reimbursement2008< 32040 91   47 B2 (0.066 0.48 0.19 0.23 0.033)  
##                        2044) age>=72 47   22 B2 (0.064 0.53 0.21 0.13 0.064)  
##                          4088) osteoporosis< 0.5 30   10 B2 (0.067 0.67 0.067 0.13 0.067) *
##                          4089) osteoporosis>=0.5 17    9 B3 (0.059 0.29 0.47 0.12 0.059) *
##                        2045) age< 72 44   25 B2 (0.068 0.43 0.16 0.34 0)  
##                          4090) alzheimers< 0.5 11    4 B2 (0.091 0.64 0.18 0.091 0) *
##                          4091) alzheimers>=0.5 33   19 B4 (0.061 0.36 0.15 0.42 0)  
##                            8182) arthritis>=0.5 17    8 B2 (0 0.53 0.059 0.41 0) *
##                            8183) arthritis< 0.5 16    9 B4 (0.12 0.19 0.25 0.44 0) *
##                      1023) reimbursement2008>=32040 331  226 B4 (0.073 0.31 0.24 0.32 0.054)  
##                        2046) stroke>=0.5 97   58 B2 (0.062 0.4 0.18 0.29 0.072)  
##                          4092) copd< 0.5 26   17 B2 (0.23 0.35 0.19 0.19 0.038)  
##                            8184) depression< 0.5 13    7 B1 (0.46 0.15 0.15 0.15 0.077) *
##                            8185) depression>=0.5 13    6 B2 (0 0.54 0.23 0.23 0) *
##                          4093) copd>=0.5 71   41 B2 (0 0.42 0.17 0.32 0.085)  
##                            8186) reimbursement2008< 38625 13    7 B2 (0 0.46 0.38 0.077 0.077) *
##                            8187) reimbursement2008>=38625 58   34 B2 (0 0.41 0.12 0.38 0.086)  
##                             16374) age< 79.5 39   20 B2 (0 0.49 0.077 0.44 0)  
##                               32748) age>=63.5 26   12 B2 (0 0.54 0.12 0.35 0) *
##                               32749) age< 63.5 13    5 B4 (0 0.38 0 0.62 0) *
##                             16375) age>=79.5 19   14 B2 (0 0.26 0.21 0.26 0.26) *
##                        2047) stroke< 0.5 234  157 B4 (0.077 0.28 0.27 0.33 0.047)  
##                          4094) reimbursement2008>=37290 180  126 B2 (0.078 0.3 0.29 0.28 0.044)  
##                            8188) age< 82.5 150  101 B2 (0.093 0.33 0.28 0.25 0.047)  
##                             16376) reimbursement2008< 88685 139   91 B2 (0.1 0.35 0.26 0.26 0.036)  
##                               32752) reimbursement2008>=79435 7    2 B2 (0 0.71 0 0.29 0) *
##                               32753) reimbursement2008< 79435 132   89 B2 (0.11 0.33 0.27 0.26 0.038)  
##                                 65506) age>=68.5 72   48 B2 (0.15 0.33 0.19 0.28 0.042)  
##                                  131012) heart.failure>=0.5 65   41 B2 (0.14 0.37 0.2 0.25 0.046)  
##                                    262024) age>=72.5 46   27 B2 (0.11 0.41 0.24 0.17 0.065)  
##                                      524048) reimbursement2008>=52775 25   16 B2 (0.16 0.36 0.36 0.08 0.04)  
##                                       1048096) reimbursement2008>=59785 11    7 B1 (0.36 0.36 0.091 0.18 0) *
##                                       1048097) reimbursement2008< 59785 14    6 B3 (0 0.36 0.57 0 0.071) *
##                                      524049) reimbursement2008< 52775 21   11 B2 (0.048 0.48 0.095 0.29 0.095)  
##                                       1048098) copd< 0.5 7    1 B2 (0 0.86 0 0.14 0) *
##                                       1048099) copd>=0.5 14    9 B4 (0.071 0.29 0.14 0.36 0.14) *
##                                    262025) age< 72.5 19   11 B4 (0.21 0.26 0.11 0.42 0) *
##                                  131013) heart.failure< 0.5 7    3 B4 (0.29 0 0.14 0.57 0) *
##                                 65507) age< 68.5 60   38 B3 (0.05 0.32 0.37 0.23 0.033)  
##                                  131014) osteoporosis< 0.5 38   20 B3 (0.053 0.26 0.47 0.18 0.026)  
##                                    262028) reimbursement2008< 44435 16    6 B3 (0.12 0.12 0.62 0.12 0) *
##                                    262029) reimbursement2008>=44435 22   14 B2 (0 0.36 0.36 0.23 0.045)  
##                                      524058) depression>=0.5 12    6 B2 (0 0.5 0.17 0.25 0.083) *
##                                      524059) depression< 0.5 10    4 B3 (0 0.2 0.6 0.2 0) *
##                                  131015) osteoporosis>=0.5 22   13 B2 (0.045 0.41 0.18 0.32 0.045)  
##                                    262030) depression< 0.5 8    3 B2 (0.12 0.62 0.12 0.12 0) *
##                                    262031) depression>=0.5 14    8 B4 (0 0.29 0.21 0.43 0.071) *
##                             16377) reimbursement2008>=88685 11    5 B3 (0 0.091 0.55 0.18 0.18) *
##                            8189) age>=82.5 30   17 B4 (0 0.17 0.37 0.43 0.033)  
##                             16378) copd< 0.5 9    5 B3 (0 0.22 0.44 0.22 0.11) *
##                             16379) copd>=0.5 21   10 B4 (0 0.14 0.33 0.52 0)  
##                               32758) depression>=0.5 10    5 B3 (0 0.1 0.5 0.4 0) *
##                               32759) depression< 0.5 11    4 B4 (0 0.18 0.18 0.64 0) *
##                          4095) reimbursement2008< 37290 54   28 B4 (0.074 0.2 0.19 0.48 0.056)  
##                            8190) reimbursement2008< 35865 39   25 B4 (0.1 0.26 0.21 0.36 0.077)  
##                             16380) depression>=0.5 27   19 B2 (0.074 0.3 0.3 0.3 0.037)  
##                               32760) age>=70 19   12 B3 (0.11 0.32 0.37 0.21 0) *
##                               32761) age< 70 8    4 B4 (0 0.25 0.12 0.5 0.12) *
##                             16381) depression< 0.5 12    6 B4 (0.17 0.17 0 0.5 0.17) *
##                            8191) reimbursement2008>=35865 15    3 B4 (0 0.067 0.13 0.8 0) *
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12588   654   148    36     0
##        B2  1419  2122   203    59     0
##        B3   767   486   488    48     0
##        B4   336   279    99   153     0
##        B5    41    49    15    10     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.675500e-01   4.861839e-01   7.616324e-01   7.733898e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##  3.187284e-196  1.002543e-280 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 11972  1166   232    56     0
##        B2  1955  1384   367    98     0
##        B3   889   657   183    60     0
##        B4   346   349   114    57     0
##        B5    39    48    18    10     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   6.798000e-01   2.897201e-01   6.732832e-01   6.862645e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   5.289133e-03  1.795989e-240 
##                      model_id model_method
## 1 All.X.lser.no.cp.4015.rpart        rpart
##                                                                                                                                             feats
## 1 age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
##   max.nTuningRuns min.elapsedtime.everything min.elapsedtime.final
## 1               1                      5.426                 0.914
##   max.Accuracy.fit max.AccuracyLower.fit max.AccuracyUpper.fit
## 1        0.6782992             0.7616324             0.7733898
##   max.Kappa.fit max.Accuracy.OOB max.AccuracyLower.OOB
## 1      0.292721           0.6798             0.6732832
##   max.AccuracyUpper.OOB max.Kappa.OOB min.SSE.fit max.AccuracySD.fit
## 1             0.6862645     0.2897201           0        0.006853054
##   max.KappaSD.fit
## 1      0.01455375
## [1] "fitting model: All.X.lser.ys.cp.opt.rpart"
## [1] "    indep_vars: age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008"
## + Fold1: cp=0.00502 
## - Fold1: cp=0.00502 
## + Fold2: cp=0.00502 
## - Fold2: cp=0.00502 
## + Fold3: cp=0.00502 
## - Fold3: cp=0.00502 
## + Fold4: cp=0.00502 
## - Fold4: cp=0.00502 
## + Fold5: cp=0.00502 
## - Fold5: cp=0.00502 
## Aggregating results
## Selecting tuning parameters
## Fitting cp = 0.017 on full training set

## Call:
## rpart(formula = .outcome ~ ., control = list(minsplit = 20, minbucket = 7, 
##     cp = 0, maxcompete = 4, maxsurrogate = 5, usesurrogate = 2, 
##     surrogatestyle = 0, maxdepth = 30, xval = 0))
##   n= 20000 
## 
##           CP nsplit rel error
## 1 0.04677517      0 1.0000000
## 2 0.01703681      2 0.9064497
## 
## Variable importance
## reimbursement2008        bucket2008               ihd          diabetes 
##                31                21                14                13 
##     heart.failure            kidney 
##                12                 9 
## 
## Node number 1: 20000 observations,    complexity param=0.04677517
##   predicted class=B1  expected loss=0.3287  P(node) =1
##     class counts: 13426  3803  1789   867   115
##    probabilities: 0.671 0.190 0.089 0.043 0.006 
##   left son=2 (12142 obs) right son=3 (7858 obs)
##   Primary splits:
##       reimbursement2008 < 1565 to the left,  improve=1764.3490, (0 missing)
##       bucket2008        < 1.5  to the left,  improve=1460.0660, (0 missing)
##       ihd               < 0.5  to the left,  improve=1206.8110, (0 missing)
##       diabetes          < 0.5  to the left,  improve=1184.0260, (0 missing)
##       heart.failure     < 0.5  to the left,  improve= 934.8263, (0 missing)
##   Surrogate splits:
##       bucket2008    < 1.5  to the left,  agree=0.862, adj=0.650, (0 split)
##       ihd           < 0.5  to the left,  agree=0.790, adj=0.466, (0 split)
##       diabetes      < 0.5  to the left,  agree=0.784, adj=0.449, (0 split)
##       heart.failure < 0.5  to the left,  agree=0.763, adj=0.397, (0 split)
##       kidney        < 0.5  to the left,  agree=0.732, adj=0.319, (0 split)
## 
## Node number 2: 12142 observations
##   predicted class=B1  expected loss=0.1275737  P(node) =0.6071
##     class counts: 10593   933   433   164    19
##    probabilities: 0.872 0.077 0.036 0.014 0.002 
## 
## Node number 3: 7858 observations,    complexity param=0.04677517
##   predicted class=B2  expected loss=0.6347671  P(node) =0.3929
##     class counts:  2833  2870  1356   703    96
##    probabilities: 0.361 0.365 0.173 0.089 0.012 
##   left son=6 (3262 obs) right son=7 (4596 obs)
##   Primary splits:
##       reimbursement2008 < 3425 to the left,  improve=138.79980, (0 missing)
##       bucket2008        < 1.5  to the left,  improve=127.82570, (0 missing)
##       kidney            < 0.5  to the left,  improve=108.01160, (0 missing)
##       diabetes          < 0.5  to the left,  improve= 91.30944, (0 missing)
##       ihd               < 0.5  to the left,  improve= 83.33736, (0 missing)
##   Surrogate splits:
##       bucket2008    < 1.5  to the left,  agree=0.935, adj=0.844, (0 split)
##       heart.failure < 0.5  to the left,  agree=0.636, adj=0.122, (0 split)
##       kidney        < 0.5  to the left,  agree=0.634, adj=0.117, (0 split)
##       ihd           < 0.5  to the left,  agree=0.631, adj=0.111, (0 split)
##       diabetes      < 0.5  to the left,  agree=0.623, adj=0.092, (0 split)
## 
## Node number 6: 3262 observations
##   predicted class=B1  expected loss=0.5012262  P(node) =0.1631
##     class counts:  1627  1049   415   155    16
##    probabilities: 0.499 0.322 0.127 0.048 0.005 
## 
## Node number 7: 4596 observations
##   predicted class=B2  expected loss=0.6037859  P(node) =0.2298
##     class counts:  1206  1821   941   548    80
##    probabilities: 0.262 0.396 0.205 0.119 0.017 
## 
## n= 20000 
## 
## node), split, n, loss, yval, (yprob)
##       * denotes terminal node
## 
## 1) root 20000 6574 B1 (0.67 0.19 0.089 0.043 0.0057)  
##   2) reimbursement2008< 1565 12142 1549 B1 (0.87 0.077 0.036 0.014 0.0016) *
##   3) reimbursement2008>=1565 7858 4988 B2 (0.36 0.37 0.17 0.089 0.012)  
##     6) reimbursement2008< 3425 3262 1635 B1 (0.5 0.32 0.13 0.048 0.0049) *
##     7) reimbursement2008>=3425 4596 2775 B2 (0.26 0.4 0.2 0.12 0.017) *
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12220  1206     0     0     0
##        B2  1982  1821     0     0     0
##        B3   848   941     0     0     0
##        B4   319   548     0     0     0
##        B5    35    80     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.020500e-01   3.217129e-01   6.956574e-01   7.083838e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   5.406392e-21            NaN 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12274  1152     0     0     0
##        B2  1961  1843     0     0     0
##        B3   849   940     0     0     0
##        B4   327   539     0     0     0
##        B5    39    76     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.058500e-01   3.286550e-01   6.994804e-01   7.121597e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   4.639660e-26            NaN 
##                     model_id model_method
## 1 All.X.lser.ys.cp.opt.rpart        rpart
##                                                                                                                                             feats
## 1 age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
##   max.nTuningRuns min.elapsedtime.everything min.elapsedtime.final
## 1               3                      7.386                 0.917
##   max.Accuracy.fit max.AccuracyLower.fit max.AccuracyUpper.fit
## 1          0.70205             0.6956574             0.7083838
##   max.Kappa.fit min.loss.error.fit max.Accuracy.OOB max.AccuracyLower.OOB
## 1     0.3217129          0.7768504          0.70585             0.6994804
##   max.AccuracyUpper.OOB max.Kappa.OOB min.loss.error.OOB min.SSE.fit
## 1             0.7121597      0.328655             0.7618           0
##   min.loss.errorSD.fit
## 1           0.01485311
## [1] "fitting model: All.X.lser.ys.cp.4015.rpart"
## [1] "    indep_vars: age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008"
## + Fold1: cp=5e-05 
## - Fold1: cp=5e-05 
## + Fold2: cp=5e-05 
## - Fold2: cp=5e-05 
## + Fold3: cp=5e-05 
## - Fold3: cp=5e-05 
## + Fold4: cp=5e-05 
## - Fold4: cp=5e-05 
## + Fold5: cp=5e-05 
## - Fold5: cp=5e-05 
## Aggregating results
## Fitting final model on full training set
## Warning: labs do not fit even at cex 0.15, there may be some overplotting

## Call:
## rpart(formula = .outcome ~ ., control = list(minsplit = 20, minbucket = 7, 
##     cp = 0, maxcompete = 4, maxsurrogate = 5, usesurrogate = 2, 
##     surrogatestyle = 0, maxdepth = 30, xval = 0))
##   n= 20000 
## 
##              CP nsplit rel error
## 1  4.677517e-02      0 1.0000000
## 2  1.703681e-02      2 0.9064497
## 3  5.019775e-03      3 0.8894128
## 4  3.346517e-03      4 0.8843931
## 5  2.053544e-03      7 0.8743535
## 6  1.216915e-03      9 0.8702464
## 7  1.064801e-03     11 0.8678126
## 8  9.126863e-04     16 0.8624886
## 9  8.746577e-04     17 0.8615759
## 10 8.619815e-04     26 0.8522969
## 11 7.605720e-04     29 0.8497110
## 12 6.084576e-04     34 0.8459081
## 13 5.324004e-04     44 0.8398235
## 14 5.070480e-04     50 0.8366291
## 15 4.563432e-04     83 0.8183754
## 16 4.056384e-04    110 0.8060542
## 17 3.802860e-04    115 0.8039246
## 18 3.650745e-04    134 0.7966231
## 19 3.549336e-04    144 0.7928202
## 20 3.422574e-04    164 0.7852145
## 21 3.295812e-04    168 0.7838455
## 22 3.042288e-04    174 0.7818680
## 23 2.788764e-04    222 0.7671129
## 24 2.738059e-04    230 0.7648312
## 25 2.662002e-04    238 0.7620931
## 26 2.535240e-04    246 0.7599635
## 27 2.281716e-04    262 0.7555522
## 28 2.028192e-04    301 0.7449042
## 29 1.901430e-04    329 0.7380590
## 30 1.521144e-04    345 0.7345604
## 31 1.303838e-04    438 0.7191968
## 32 1.216915e-04    445 0.7182841
## 33 1.014096e-04    459 0.7161545
## 34 8.450799e-05    475 0.7143292
## 35 7.605720e-05    485 0.7134165
## 36 6.519188e-05    527 0.7102221
## 37 6.084576e-05    560 0.7079404
## 38 5.070480e-05    567 0.7074840
## 39 5.000000e-05    573 0.7071798
## 
## Variable importance
## reimbursement2008        bucket2008          diabetes               ihd 
##                32                17                12                12 
##     heart.failure            kidney               age        depression 
##                10                 8                 4                 1 
##      osteoporosis              copd         arthritis        alzheimers 
##                 1                 1                 1                 1 
## 
## Node number 1: 20000 observations,    complexity param=0.04677517
##   predicted class=B1  expected loss=0.3287  P(node) =1
##     class counts: 13426  3803  1789   867   115
##    probabilities: 0.671 0.190 0.089 0.043 0.006 
##   left son=2 (12142 obs) right son=3 (7858 obs)
##   Primary splits:
##       reimbursement2008 < 1565   to the left,  improve=1764.3490, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=1460.0660, (0 missing)
##       ihd               < 0.5    to the left,  improve=1206.8110, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1184.0260, (0 missing)
##       heart.failure     < 0.5    to the left,  improve= 934.8263, (0 missing)
##   Surrogate splits:
##       bucket2008    < 1.5    to the left,  agree=0.862, adj=0.650, (0 split)
##       ihd           < 0.5    to the left,  agree=0.790, adj=0.466, (0 split)
##       diabetes      < 0.5    to the left,  agree=0.784, adj=0.449, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.763, adj=0.397, (0 split)
##       kidney        < 0.5    to the left,  agree=0.732, adj=0.319, (0 split)
## 
## Node number 2: 12142 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.1275737  P(node) =0.6071
##     class counts: 10593   933   433   164    19
##    probabilities: 0.872 0.077 0.036 0.014 0.002 
##   left son=4 (6456 obs) right son=5 (5686 obs)
##   Primary splits:
##       reimbursement2008 < 195    to the left,  improve=186.28990, (0 missing)
##       diabetes          < 0.5    to the left,  improve=101.76450, (0 missing)
##       ihd               < 0.5    to the left,  improve= 95.31422, (0 missing)
##       heart.failure     < 0.5    to the left,  improve= 56.11198, (0 missing)
##       depression        < 0.5    to the left,  improve= 42.49380, (0 missing)
##   Surrogate splits:
##       ihd           < 0.5    to the left,  agree=0.707, adj=0.374, (0 split)
##       diabetes      < 0.5    to the left,  agree=0.692, adj=0.343, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.630, adj=0.209, (0 split)
##       depression    < 0.5    to the left,  agree=0.608, adj=0.163, (0 split)
##       osteoporosis  < 0.5    to the left,  agree=0.606, adj=0.158, (0 split)
## 
## Node number 3: 7858 observations,    complexity param=0.04677517
##   predicted class=B2  expected loss=0.6347671  P(node) =0.3929
##     class counts:  2833  2870  1356   703    96
##    probabilities: 0.361 0.365 0.173 0.089 0.012 
##   left son=6 (3262 obs) right son=7 (4596 obs)
##   Primary splits:
##       reimbursement2008 < 3425   to the left,  improve=138.79980, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=127.82570, (0 missing)
##       kidney            < 0.5    to the left,  improve=108.01160, (0 missing)
##       diabetes          < 0.5    to the left,  improve= 91.30944, (0 missing)
##       ihd               < 0.5    to the left,  improve= 83.33736, (0 missing)
##   Surrogate splits:
##       bucket2008    < 1.5    to the left,  agree=0.935, adj=0.844, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.636, adj=0.122, (0 split)
##       kidney        < 0.5    to the left,  agree=0.634, adj=0.117, (0 split)
##       ihd           < 0.5    to the left,  agree=0.631, adj=0.111, (0 split)
##       diabetes      < 0.5    to the left,  agree=0.623, adj=0.092, (0 split)
## 
## Node number 4: 6456 observations
##   predicted class=B1  expected loss=0.03175341  P(node) =0.3228
##     class counts:  6251   108    69    25     3
##    probabilities: 0.968 0.017 0.011 0.004 0.000 
## 
## Node number 5: 5686 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.23637  P(node) =0.2843
##     class counts:  4342   825   364   139    16
##    probabilities: 0.764 0.145 0.064 0.024 0.003 
##   left son=10 (2374 obs) right son=11 (3312 obs)
##   Primary splits:
##       reimbursement2008 < 685    to the left,  improve=27.349520, (0 missing)
##       diabetes          < 0.5    to the left,  improve=17.262440, (0 missing)
##       ihd               < 0.5    to the left,  improve=13.874990, (0 missing)
##       heart.failure     < 0.5    to the left,  improve= 8.237337, (0 missing)
##       depression        < 0.5    to the left,  improve= 7.708074, (0 missing)
##   Surrogate splits:
##       diabetes < 0.5    to the left,  agree=0.586, adj=0.008, (0 split)
## 
## Node number 6: 3262 observations,    complexity param=0.003346517
##   predicted class=B1  expected loss=0.5012262  P(node) =0.1631
##     class counts:  1627  1049   415   155    16
##    probabilities: 0.499 0.322 0.127 0.048 0.005 
##   left son=12 (1087 obs) right son=13 (2175 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=22.12235, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=18.39133, (0 missing)
##       kidney            < 0.5    to the left,  improve=16.45818, (0 missing)
##       reimbursement2008 < 2535   to the left,  improve=15.04368, (0 missing)
##       arthritis         < 0.5    to the left,  improve=14.50169, (0 missing)
## 
## Node number 7: 4596 observations,    complexity param=0.01703681
##   predicted class=B2  expected loss=0.6037859  P(node) =0.2298
##     class counts:  1206  1821   941   548    80
##    probabilities: 0.262 0.396 0.205 0.119 0.017 
##   left son=14 (1002 obs) right son=15 (3594 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=54.64315, (0 missing)
##       kidney            < 0.5    to the left,  improve=39.83945, (0 missing)
##       arthritis         < 0.5    to the left,  improve=27.98163, (0 missing)
##       ihd               < 0.5    to the left,  improve=27.96369, (0 missing)
##       reimbursement2008 < 14985  to the left,  improve=24.59678, (0 missing)
## 
## Node number 10: 2374 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1693345  P(node) =0.1187
##     class counts:  1972   239   123    35     5
##    probabilities: 0.831 0.101 0.052 0.015 0.002 
##   left son=20 (1860 obs) right son=21 (514 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=2.303753, (0 missing)
##       reimbursement2008 < 415    to the left,  improve=1.555073, (0 missing)
##       age               < 89.5   to the left,  improve=1.295020, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.286801, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.280980, (0 missing)
## 
## Node number 11: 3312 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.2844203  P(node) =0.1656
##     class counts:  2370   586   241   104    11
##    probabilities: 0.716 0.177 0.073 0.031 0.003 
##   left son=22 (1722 obs) right son=23 (1590 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=7.957796, (0 missing)
##       diabetes          < 0.5    to the left,  improve=6.966093, (0 missing)
##       reimbursement2008 < 1185   to the left,  improve=5.843071, (0 missing)
##       kidney            < 0.5    to the left,  improve=4.261749, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=4.259057, (0 missing)
##   Surrogate splits:
##       heart.failure     < 0.5    to the left,  agree=0.581, adj=0.127, (0 split)
##       diabetes          < 0.5    to the left,  agree=0.570, adj=0.104, (0 split)
##       reimbursement2008 < 1285   to the left,  agree=0.551, adj=0.065, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.542, adj=0.045, (0 split)
##       kidney            < 0.5    to the left,  agree=0.542, adj=0.045, (0 split)
## 
## Node number 12: 1087 observations,    complexity param=0.000760572
##   predicted class=B1  expected loss=0.4066237  P(node) =0.05435
##     class counts:   645   279   123    36     4
##    probabilities: 0.593 0.257 0.113 0.033 0.004 
##   left son=24 (941 obs) right son=25 (146 obs)
##   Primary splits:
##       kidney        < 0.5    to the left,  improve=6.950529, (0 missing)
##       heart.failure < 0.5    to the left,  improve=5.539453, (0 missing)
##       copd          < 0.5    to the left,  improve=3.363659, (0 missing)
##       diabetes      < 0.5    to the left,  improve=3.245895, (0 missing)
##       osteoporosis  < 0.5    to the left,  improve=2.285942, (0 missing)
## 
## Node number 13: 2175 observations,    complexity param=0.003346517
##   predicted class=B1  expected loss=0.5485057  P(node) =0.10875
##     class counts:   982   770   292   119    12
##    probabilities: 0.451 0.354 0.134 0.055 0.006 
##   left son=26 (1275 obs) right son=27 (900 obs)
##   Primary splits:
##       reimbursement2008 < 2515   to the left,  improve=11.475830, (0 missing)
##       arthritis         < 0.5    to the left,  improve=10.277840, (0 missing)
##       heart.failure     < 0.5    to the left,  improve= 7.801216, (0 missing)
##       kidney            < 0.5    to the left,  improve= 7.393483, (0 missing)
##       bucket2008        < 1.5    to the left,  improve= 6.716155, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.762, adj=0.426, (0 split)
##       copd       < 0.5    to the left,  agree=0.592, adj=0.013, (0 split)
##       age        < 33     to the right, agree=0.590, adj=0.010, (0 split)
## 
## Node number 14: 1002 observations,    complexity param=0.005019775
##   predicted class=B1  expected loss=0.5568862  P(node) =0.0501
##     class counts:   444   332   169    54     3
##    probabilities: 0.443 0.331 0.169 0.054 0.003 
##   left son=28 (682 obs) right son=29 (320 obs)
##   Primary splits:
##       depression   < 0.5    to the left,  improve=13.412950, (0 missing)
##       cancer       < 0.5    to the left,  improve= 8.676806, (0 missing)
##       osteoporosis < 0.5    to the left,  improve= 6.334493, (0 missing)
##       arthritis    < 0.5    to the left,  improve= 6.023249, (0 missing)
##       ihd          < 0.5    to the left,  improve= 5.212491, (0 missing)
##   Surrogate splits:
##       age < 49.5   to the right, agree=0.682, adj=0.003, (0 split)
## 
## Node number 15: 3594 observations,    complexity param=0.0008746577
##   predicted class=B2  expected loss=0.5856984  P(node) =0.1797
##     class counts:   762  1489   772   494    77
##    probabilities: 0.212 0.414 0.215 0.137 0.021 
##   left son=30 (1568 obs) right son=31 (2026 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=29.54937, (0 missing)
##       reimbursement2008 < 14405  to the left,  improve=18.69161, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=16.83945, (0 missing)
##       arthritis         < 0.5    to the left,  improve=15.87697, (0 missing)
##       ihd               < 0.5    to the left,  improve=11.13037, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 7325   to the left,  agree=0.660, adj=0.220, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.658, adj=0.217, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.633, adj=0.159, (0 split)
##       ihd               < 0.5    to the left,  agree=0.598, adj=0.078, (0 split)
##       copd              < 0.5    to the left,  agree=0.593, adj=0.067, (0 split)
## 
## Node number 20: 1860 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1553763  P(node) =0.093
##     class counts:  1571   176    86    23     4
##    probabilities: 0.845 0.095 0.046 0.012 0.002 
##   left son=40 (1774 obs) right son=41 (86 obs)
##   Primary splits:
##       age               < 89.5   to the left,  improve=1.8556120, (0 missing)
##       reimbursement2008 < 665    to the left,  improve=0.6577829, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.6342891, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5532770, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5456541, (0 missing)
## 
## Node number 21: 514 observations,    complexity param=5.07048e-05
##   predicted class=B1  expected loss=0.2198444  P(node) =0.0257
##     class counts:   401    63    37    12     1
##    probabilities: 0.780 0.123 0.072 0.023 0.002 
##   left son=42 (173 obs) right son=43 (341 obs)
##   Primary splits:
##       reimbursement2008 < 425    to the left,  improve=1.4829330, (0 missing)
##       age               < 94.5   to the right, improve=0.8488381, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5210342, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.4383554, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.3942705, (0 missing)
##   Surrogate splits:
##       age < 98.5   to the right, agree=0.671, adj=0.023, (0 split)
## 
## Node number 22: 1722 observations,    complexity param=0.0001303838
##   predicted class=B1  expected loss=0.2462253  P(node) =0.0861
##     class counts:  1298   261   107    51     5
##    probabilities: 0.754 0.152 0.062 0.030 0.003 
##   left son=44 (951 obs) right son=45 (771 obs)
##   Primary splits:
##       reimbursement2008 < 1085   to the left,  improve=2.133022, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.851709, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.814680, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.791298, (0 missing)
##       depression        < 0.5    to the left,  improve=1.477471, (0 missing)
##   Surrogate splits:
##       kidney       < 0.5    to the left,  agree=0.569, adj=0.038, (0 split)
##       osteoporosis < 0.5    to the left,  agree=0.562, adj=0.022, (0 split)
##       arthritis    < 0.5    to the left,  agree=0.560, adj=0.017, (0 split)
##       diabetes     < 0.5    to the left,  agree=0.560, adj=0.017, (0 split)
##       depression   < 0.5    to the left,  agree=0.559, adj=0.016, (0 split)
## 
## Node number 23: 1590 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.3257862  P(node) =0.0795
##     class counts:  1072   325   134    53     6
##    probabilities: 0.674 0.204 0.084 0.033 0.004 
##   left son=46 (771 obs) right son=47 (819 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=3.574744, (0 missing)
##       reimbursement2008 < 1285   to the left,  improve=3.467285, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=2.297182, (0 missing)
##       age               < 27.5   to the right, improve=1.741472, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.681255, (0 missing)
##   Surrogate splits:
##       heart.failure     < 0.5    to the left,  agree=0.550, adj=0.073, (0 split)
##       reimbursement2008 < 1145   to the left,  agree=0.545, adj=0.061, (0 split)
##       kidney            < 0.5    to the left,  agree=0.535, adj=0.040, (0 split)
##       age               < 76.5   to the left,  agree=0.528, adj=0.026, (0 split)
##       depression        < 0.5    to the left,  agree=0.522, adj=0.014, (0 split)
## 
## Node number 24: 941 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.3804463  P(node) =0.04705
##     class counts:   583   229    96    29     4
##    probabilities: 0.620 0.243 0.102 0.031 0.004 
##   left son=48 (680 obs) right son=49 (261 obs)
##   Primary splits:
##       heart.failure < 0.5    to the left,  improve=4.641423, (0 missing)
##       diabetes      < 0.5    to the left,  improve=2.866491, (0 missing)
##       osteoporosis  < 0.5    to the left,  improve=1.985004, (0 missing)
##       copd          < 0.5    to the left,  improve=1.760285, (0 missing)
##       age           < 52.5   to the left,  improve=1.424379, (0 missing)
## 
## Node number 25: 146 observations,    complexity param=0.000760572
##   predicted class=B1  expected loss=0.5753425  P(node) =0.0073
##     class counts:    62    50    27     7     0
##    probabilities: 0.425 0.342 0.185 0.048 0.000 
##   left son=50 (82 obs) right son=51 (64 obs)
##   Primary splits:
##       age               < 74.5   to the left,  improve=3.6513430, (0 missing)
##       reimbursement2008 < 3080   to the right, improve=2.1345630, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.2427630, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.0530420, (0 missing)
##       copd              < 0.5    to the left,  improve=0.9560376, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1765   to the right, agree=0.575, adj=0.031, (0 split)
## 
## Node number 26: 1275 observations,    complexity param=0.001064801
##   predicted class=B1  expected loss=0.4996078  P(node) =0.06375
##     class counts:   638   409   152    68     8
##    probabilities: 0.500 0.321 0.119 0.053 0.006 
##   left son=52 (880 obs) right son=53 (395 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=5.193576, (0 missing)
##       reimbursement2008 < 1765   to the left,  improve=4.667403, (0 missing)
##       age               < 80.5   to the right, improve=3.217982, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=2.254540, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.756421, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2495   to the left,  agree=0.693, adj=0.008, (0 split)
## 
## Node number 27: 900 observations,    complexity param=0.003346517
##   predicted class=B2  expected loss=0.5988889  P(node) =0.045
##     class counts:   344   361   140    51     4
##    probabilities: 0.382 0.401 0.156 0.057 0.004 
##   left son=54 (614 obs) right son=55 (286 obs)
##   Primary splits:
##       arthritis     < 0.5    to the left,  improve=9.449426, (0 missing)
##       heart.failure < 0.5    to the left,  improve=7.177110, (0 missing)
##       kidney        < 0.5    to the left,  improve=4.982522, (0 missing)
##       copd          < 0.5    to the left,  improve=3.774501, (0 missing)
##       cancer        < 0.5    to the left,  improve=3.018782, (0 missing)
##   Surrogate splits:
##       age < 37.5   to the right, agree=0.687, adj=0.014, (0 split)
## 
## Node number 28: 682 observations,    complexity param=0.001216915
##   predicted class=B1  expected loss=0.4912023  P(node) =0.0341
##     class counts:   347   202    97    33     3
##    probabilities: 0.509 0.296 0.142 0.048 0.004 
##   left son=56 (563 obs) right son=57 (119 obs)
##   Primary splits:
##       cancer            < 0.5    to the left,  improve=8.288699, (0 missing)
##       arthritis         < 0.5    to the left,  improve=4.176438, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=3.934963, (0 missing)
##       ihd               < 0.5    to the left,  improve=3.166893, (0 missing)
##       reimbursement2008 < 8450   to the right, improve=2.733079, (0 missing)
## 
## Node number 29: 320 observations,    complexity param=0.0008619815
##   predicted class=B2  expected loss=0.59375  P(node) =0.016
##     class counts:    97   130    72    21     0
##    probabilities: 0.303 0.406 0.225 0.066 0.000 
##   left son=58 (213 obs) right son=59 (107 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.166497, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.990034, (0 missing)
##       age               < 91.5   to the right, improve=1.926250, (0 missing)
##       reimbursement2008 < 3710   to the left,  improve=1.809690, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.730409, (0 missing)
##   Surrogate splits:
##       stroke            < 0.5    to the left,  agree=0.678, adj=0.037, (0 split)
##       reimbursement2008 < 40240  to the left,  agree=0.675, adj=0.028, (0 split)
##       age               < 42.5   to the right, agree=0.672, adj=0.019, (0 split)
##       bucket2008        < 4.5    to the left,  agree=0.669, adj=0.009, (0 split)
## 
## Node number 30: 1568 observations,    complexity param=0.0008746577
##   predicted class=B2  expected loss=0.5612245  P(node) =0.0784
##     class counts:   448   688   304   117    11
##    probabilities: 0.286 0.439 0.194 0.075 0.007 
##   left son=60 (964 obs) right son=61 (604 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=9.229921, (0 missing)
##       cancer            < 0.5    to the left,  improve=6.469383, (0 missing)
##       reimbursement2008 < 59995  to the left,  improve=4.836546, (0 missing)
##       bucket2008        < 4.5    to the left,  improve=3.876636, (0 missing)
##       age               < 71.5   to the right, improve=3.803969, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 35170  to the left,  agree=0.620, adj=0.013, (0 split)
##       bucket2008        < 4.5    to the left,  agree=0.615, adj=0.002, (0 split)
## 
## Node number 31: 2026 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6046397  P(node) =0.1013
##     class counts:   314   801   468   377    66
##    probabilities: 0.155 0.395 0.231 0.186 0.033 
##   left son=62 (1090 obs) right son=63 (936 obs)
##   Primary splits:
##       reimbursement2008 < 15095  to the left,  improve=9.838861, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=7.625303, (0 missing)
##       arthritis         < 0.5    to the left,  improve=7.497489, (0 missing)
##       ihd               < 0.5    to the left,  improve=4.354999, (0 missing)
##       age               < 44.5   to the right, improve=4.056220, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the left,  agree=0.913, adj=0.811, (0 split)
##       copd       < 0.5    to the left,  agree=0.610, adj=0.156, (0 split)
##       stroke     < 0.5    to the left,  agree=0.582, adj=0.096, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.567, adj=0.063, (0 split)
##       cancer     < 0.5    to the left,  agree=0.566, adj=0.061, (0 split)
## 
## Node number 40: 1774 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1499436  P(node) =0.0887
##     class counts:  1508   165    75    23     3
##    probabilities: 0.850 0.093 0.042 0.013 0.002 
##   left son=80 (1764 obs) right son=81 (10 obs)
##   Primary splits:
##       age               < 29.5   to the right, improve=1.1538870, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8525277, (0 missing)
##       reimbursement2008 < 665    to the left,  improve=0.6307025, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5616328, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5123385, (0 missing)
## 
## Node number 41: 86 observations
##   predicted class=B1  expected loss=0.2674419  P(node) =0.0043
##     class counts:    63    11    11     0     1
##    probabilities: 0.733 0.128 0.128 0.000 0.012 
## 
## Node number 42: 173 observations,    complexity param=5.07048e-05
##   predicted class=B1  expected loss=0.1618497  P(node) =0.00865
##     class counts:   145    13    11     4     0
##    probabilities: 0.838 0.075 0.064 0.023 0.000 
##   left son=84 (147 obs) right son=85 (26 obs)
##   Primary splits:
##       age               < 64.5   to the right, improve=2.0458370, (0 missing)
##       reimbursement2008 < 355    to the right, improve=0.9835129, (0 missing)
##       depression        < 0.5    to the right, improve=0.3524686, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.3137783, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.2903122, (0 missing)
## 
## Node number 43: 341 observations
##   predicted class=B1  expected loss=0.2492669  P(node) =0.01705
##     class counts:   256    50    26     8     1
##    probabilities: 0.751 0.147 0.076 0.023 0.003 
## 
## Node number 44: 951 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2197687  P(node) =0.04755
##     class counts:   742   132    48    26     3
##    probabilities: 0.780 0.139 0.050 0.027 0.003 
##   left son=88 (811 obs) right son=89 (140 obs)
##   Primary splits:
##       alzheimers    < 0.5    to the left,  improve=1.2963180, (0 missing)
##       depression    < 0.5    to the left,  improve=1.1750410, (0 missing)
##       kidney        < 0.5    to the left,  improve=0.8204364, (0 missing)
##       diabetes      < 0.5    to the left,  improve=0.8186009, (0 missing)
##       heart.failure < 0.5    to the left,  improve=0.6649241, (0 missing)
## 
## Node number 45: 771 observations,    complexity param=0.0001303838
##   predicted class=B1  expected loss=0.2788586  P(node) =0.03855
##     class counts:   556   129    59    25     2
##    probabilities: 0.721 0.167 0.077 0.032 0.003 
##   left son=90 (758 obs) right son=91 (13 obs)
##   Primary splits:
##       stroke       < 0.5    to the left,  improve=2.8198560, (0 missing)
##       osteoporosis < 0.5    to the left,  improve=1.3510390, (0 missing)
##       age          < 67.5   to the right, improve=1.2269310, (0 missing)
##       diabetes     < 0.5    to the left,  improve=0.9157286, (0 missing)
##       kidney       < 0.5    to the left,  improve=0.7050616, (0 missing)
## 
## Node number 46: 771 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.2853437  P(node) =0.03855
##     class counts:   551   139    60    17     4
##    probabilities: 0.715 0.180 0.078 0.022 0.005 
##   left son=92 (713 obs) right son=93 (58 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=2.3312380, (0 missing)
##       reimbursement2008 < 1465   to the left,  improve=1.5865660, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.3286190, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.1740950, (0 missing)
##       age               < 39.5   to the right, improve=0.8807352, (0 missing)
## 
## Node number 47: 819 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.3638584  P(node) =0.04095
##     class counts:   521   186    74    36     2
##    probabilities: 0.636 0.227 0.090 0.044 0.002 
##   left son=94 (412 obs) right son=95 (407 obs)
##   Primary splits:
##       reimbursement2008 < 1155   to the left,  improve=4.0618270, (0 missing)
##       age               < 96.5   to the left,  improve=1.8771670, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.1124860, (0 missing)
##       depression        < 0.5    to the left,  improve=0.8927430, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.8149295, (0 missing)
##   Surrogate splits:
##       depression    < 0.5    to the left,  agree=0.537, adj=0.069, (0 split)
##       arthritis     < 0.5    to the left,  agree=0.535, adj=0.064, (0 split)
##       age           < 75.5   to the right, agree=0.530, adj=0.054, (0 split)
##       copd          < 0.5    to the left,  agree=0.523, adj=0.039, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.521, adj=0.037, (0 split)
## 
## Node number 48: 680 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.3441176  P(node) =0.034
##     class counts:   446   153    59    20     2
##    probabilities: 0.656 0.225 0.087 0.029 0.003 
##   left son=96 (524 obs) right son=97 (156 obs)
##   Primary splits:
##       reimbursement2008 < 2605   to the left,  improve=2.7829410, (0 missing)
##       age               < 96.5   to the left,  improve=1.1143550, (0 missing)
##       copd              < 0.5    to the left,  improve=1.0550180, (0 missing)
##       depression        < 0.5    to the left,  improve=1.0401960, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.9369192, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.865, adj=0.41, (0 split)
## 
## Node number 49: 261 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.4750958  P(node) =0.01305
##     class counts:   137    76    37     9     2
##    probabilities: 0.525 0.291 0.142 0.034 0.008 
##   left son=98 (110 obs) right son=99 (151 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=2.985889, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.377857, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.334625, (0 missing)
##       reimbursement2008 < 3285   to the right, improve=1.198129, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.099034, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1845   to the left,  agree=0.613, adj=0.082, (0 split)
## 
## Node number 50: 82 observations,    complexity param=0.0006084576
##   predicted class=B1  expected loss=0.4634146  P(node) =0.0041
##     class counts:    44    22    12     4     0
##    probabilities: 0.537 0.268 0.146 0.049 0.000 
##   left son=100 (63 obs) right son=101 (19 obs)
##   Primary splits:
##       age               < 63.5   to the right, improve=2.9141960, (0 missing)
##       reimbursement2008 < 3080   to the right, improve=1.7365850, (0 missing)
##       copd              < 0.5    to the left,  improve=1.5828040, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.0929760, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.7827975, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1615   to the right, agree=0.78, adj=0.053, (0 split)
## 
## Node number 51: 64 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.5625  P(node) =0.0032
##     class counts:    18    28    15     3     0
##    probabilities: 0.281 0.438 0.234 0.047 0.000 
##   left son=102 (28 obs) right son=103 (36 obs)
##   Primary splits:
##       age               < 84.5   to the right, improve=2.3010910, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.1798210, (0 missing)
##       reimbursement2008 < 2345   to the left,  improve=0.9276332, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.6452851, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5431399, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1595   to the left,  agree=0.594, adj=0.071, (0 split)
##       depression        < 0.5    to the right, agree=0.578, adj=0.036, (0 split)
## 
## Node number 52: 880 observations,    complexity param=0.0004563432
##   predicted class=B1  expected loss=0.4681818  P(node) =0.044
##     class counts:   468   257   102    46     7
##    probabilities: 0.532 0.292 0.116 0.052 0.008 
##   left son=104 (849 obs) right son=105 (31 obs)
##   Primary splits:
##       stroke            < 0.5    to the left,  improve=3.387993, (0 missing)
##       age               < 73.5   to the right, improve=3.306641, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=3.159084, (0 missing)
##       copd              < 0.5    to the left,  improve=2.787275, (0 missing)
##       reimbursement2008 < 1855   to the left,  improve=2.780152, (0 missing)
## 
## Node number 53: 395 observations,    complexity param=0.001064801
##   predicted class=B1  expected loss=0.5696203  P(node) =0.01975
##     class counts:   170   152    50    22     1
##    probabilities: 0.430 0.385 0.127 0.056 0.003 
##   left son=106 (80 obs) right son=107 (315 obs)
##   Primary splits:
##       age               < 84.5   to the right, improve=3.498056, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=2.462798, (0 missing)
##       reimbursement2008 < 1760   to the left,  improve=2.298825, (0 missing)
##       cancer            < 0.5    to the left,  improve=2.009374, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.079384, (0 missing)
## 
## Node number 54: 614 observations,    complexity param=0.002053544
##   predicted class=B1  expected loss=0.5684039  P(node) =0.0307
##     class counts:   265   216    94    37     2
##    probabilities: 0.432 0.352 0.153 0.060 0.003 
##   left son=108 (317 obs) right son=109 (297 obs)
##   Primary splits:
##       heart.failure < 0.5    to the left,  improve=5.706356, (0 missing)
##       cancer        < 0.5    to the left,  improve=3.620611, (0 missing)
##       kidney        < 0.5    to the left,  improve=2.718926, (0 missing)
##       diabetes      < 0.5    to the left,  improve=2.388979, (0 missing)
##       stroke        < 0.5    to the left,  improve=2.007035, (0 missing)
##   Surrogate splits:
##       diabetes   < 0.5    to the left,  agree=0.593, adj=0.158, (0 split)
##       copd       < 0.5    to the left,  agree=0.570, adj=0.111, (0 split)
##       kidney     < 0.5    to the left,  agree=0.559, adj=0.088, (0 split)
##       age        < 86.5   to the left,  agree=0.550, adj=0.071, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.542, adj=0.054, (0 split)
## 
## Node number 55: 286 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.493007  P(node) =0.0143
##     class counts:    79   145    46    14     2
##    probabilities: 0.276 0.507 0.161 0.049 0.007 
##   left son=110 (174 obs) right son=111 (112 obs)
##   Primary splits:
##       reimbursement2008 < 3015   to the left,  improve=3.399972, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=2.660008, (0 missing)
##       copd              < 0.5    to the left,  improve=1.954436, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.720664, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.503497, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.972, adj=0.929, (0 split)
##       age        < 47.5   to the right, agree=0.612, adj=0.009, (0 split)
## 
## Node number 56: 563 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.4476021  P(node) =0.02815
##     class counts:   311   158    71    20     3
##    probabilities: 0.552 0.281 0.126 0.036 0.005 
##   left son=112 (419 obs) right son=113 (144 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=4.749310, (0 missing)
##       ihd               < 0.5    to the left,  improve=4.117879, (0 missing)
##       reimbursement2008 < 8450   to the right, improve=2.969907, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=2.407056, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=2.354174, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 3465   to the right, agree=0.746, adj=0.007, (0 split)
## 
## Node number 57: 119 observations,    complexity param=0.0009126863
##   predicted class=B2  expected loss=0.6302521  P(node) =0.00595
##     class counts:    36    44    26    13     0
##    probabilities: 0.303 0.370 0.218 0.109 0.000 
##   left son=114 (55 obs) right son=115 (64 obs)
##   Primary splits:
##       reimbursement2008 < 6095   to the left,  improve=1.638928, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.623836, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.588552, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.103598, (0 missing)
##       copd              < 0.5    to the left,  improve=1.082200, (0 missing)
##   Surrogate splits:
##       bucket2008    < 2.5    to the left,  agree=0.798, adj=0.564, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.689, adj=0.327, (0 split)
##       ihd           < 0.5    to the left,  agree=0.655, adj=0.255, (0 split)
##       age           < 72.5   to the left,  agree=0.580, adj=0.091, (0 split)
##       kidney        < 0.5    to the left,  agree=0.580, adj=0.091, (0 split)
## 
## Node number 58: 213 observations,    complexity param=0.0008619815
##   predicted class=B2  expected loss=0.6056338  P(node) =0.01065
##     class counts:    75    84    42    12     0
##    probabilities: 0.352 0.394 0.197 0.056 0.000 
##   left son=116 (20 obs) right son=117 (193 obs)
##   Primary splits:
##       age               < 55.5   to the left,  improve=2.485799, (0 missing)
##       reimbursement2008 < 9080   to the right, improve=1.923864, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.913762, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.732394, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.683900, (0 missing)
## 
## Node number 59: 107 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.5700935  P(node) =0.00535
##     class counts:    22    46    30     9     0
##    probabilities: 0.206 0.430 0.280 0.084 0.000 
##   left son=118 (13 obs) right son=119 (94 obs)
##   Primary splits:
##       reimbursement2008 < 25420  to the right, improve=1.3314010, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.1104610, (0 missing)
##       age               < 87.5   to the left,  improve=0.9520085, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.6222856, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.6046879, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.953, adj=0.615, (0 split)
## 
## Node number 60: 964 observations,    complexity param=0.0008746577
##   predicted class=B2  expected loss=0.5923237  P(node) =0.0482
##     class counts:   324   393   182    60     5
##    probabilities: 0.336 0.408 0.189 0.062 0.005 
##   left son=120 (791 obs) right son=121 (173 obs)
##   Primary splits:
##       cancer            < 0.5    to the left,  improve=7.881057, (0 missing)
##       age               < 70.5   to the left,  improve=5.309810, (0 missing)
##       reimbursement2008 < 58515  to the left,  improve=5.164127, (0 missing)
##       bucket2008        < 4.5    to the left,  improve=4.128531, (0 missing)
##       ihd               < 0.5    to the left,  improve=3.548552, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 70655  to the left,  agree=0.823, adj=0.012, (0 split)
## 
## Node number 61: 604 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5115894  P(node) =0.0302
##     class counts:   124   295   122    57     6
##    probabilities: 0.205 0.488 0.202 0.094 0.010 
##   left son=122 (69 obs) right son=123 (535 obs)
##   Primary splits:
##       reimbursement2008 < 3875   to the left,  improve=3.786294, (0 missing)
##       depression        < 0.5    to the left,  improve=2.941959, (0 missing)
##       age               < 34     to the right, improve=1.969721, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.555014, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.351079, (0 missing)
## 
## Node number 62: 1090 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.5752294  P(node) =0.0545
##     class counts:   195   463   261   148    23
##    probabilities: 0.179 0.425 0.239 0.136 0.021 
##   left son=124 (638 obs) right son=125 (452 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=7.151203, (0 missing)
##       reimbursement2008 < 5655   to the left,  improve=3.223904, (0 missing)
##       ihd               < 0.5    to the left,  improve=2.644429, (0 missing)
##       age               < 44.5   to the right, improve=2.630564, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.756050, (0 missing)
##   Surrogate splits:
##       age < 29.5   to the right, agree=0.589, adj=0.009, (0 split)
## 
## Node number 63: 936 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6388889  P(node) =0.0468
##     class counts:   119   338   207   229    43
##    probabilities: 0.127 0.361 0.221 0.245 0.046 
##   left son=126 (53 obs) right son=127 (883 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=2.996452, (0 missing)
##       reimbursement2008 < 26375  to the left,  improve=2.908218, (0 missing)
##       age               < 65.5   to the right, improve=2.302986, (0 missing)
##       copd              < 0.5    to the left,  improve=2.090686, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.919244, (0 missing)
## 
## Node number 80: 1764 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1485261  P(node) =0.0882
##     class counts:  1502   162    75    22     3
##    probabilities: 0.851 0.092 0.043 0.012 0.002 
##   left son=160 (1586 obs) right son=161 (178 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=0.9323517, (0 missing)
##       age               < 71.5   to the left,  improve=0.7839176, (0 missing)
##       reimbursement2008 < 665    to the left,  improve=0.6933809, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5712541, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5496311, (0 missing)
## 
## Node number 81: 10 observations
##   predicted class=B1  expected loss=0.4  P(node) =0.0005
##     class counts:     6     3     0     1     0
##    probabilities: 0.600 0.300 0.000 0.100 0.000 
## 
## Node number 84: 147 observations
##   predicted class=B1  expected loss=0.122449  P(node) =0.00735
##     class counts:   129     9     7     2     0
##    probabilities: 0.878 0.061 0.048 0.014 0.000 
## 
## Node number 85: 26 observations,    complexity param=5.07048e-05
##   predicted class=B1  expected loss=0.3846154  P(node) =0.0013
##     class counts:    16     4     4     2     0
##    probabilities: 0.615 0.154 0.154 0.077 0.000 
##   left son=170 (19 obs) right son=171 (7 obs)
##   Primary splits:
##       reimbursement2008 < 250    to the right, improve=1.9872760, (0 missing)
##       age               < 56.5   to the left,  improve=0.3934732, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.3076923, (0 missing)
## 
## Node number 88: 811 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2083847  P(node) =0.04055
##     class counts:   642   105    38    24     2
##    probabilities: 0.792 0.129 0.047 0.030 0.002 
##   left son=176 (544 obs) right son=177 (267 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=1.0063530, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9333841, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.7386915, (0 missing)
##       reimbursement2008 < 905    to the left,  improve=0.5328549, (0 missing)
##       age               < 95     to the right, improve=0.4748885, (0 missing)
##   Surrogate splits:
##       kidney            < 0.5    to the left,  agree=0.691, adj=0.060, (0 split)
##       copd              < 0.5    to the left,  agree=0.684, adj=0.041, (0 split)
##       reimbursement2008 < 1075   to the left,  agree=0.677, adj=0.019, (0 split)
##       stroke            < 0.5    to the left,  agree=0.676, adj=0.015, (0 split)
##       age               < 98.5   to the left,  agree=0.672, adj=0.004, (0 split)
## 
## Node number 89: 140 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2857143  P(node) =0.007
##     class counts:   100    27    10     2     1
##    probabilities: 0.714 0.193 0.071 0.014 0.007 
##   left son=178 (133 obs) right son=179 (7 obs)
##   Primary splits:
##       age               < 91.5   to the left,  improve=1.9225560, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.7529606, (0 missing)
##       reimbursement2008 < 715    to the left,  improve=0.6604396, (0 missing)
##       copd              < 0.5    to the right, improve=0.5219780, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.5090226, (0 missing)
## 
## Node number 90: 758 observations,    complexity param=0.0001303838
##   predicted class=B1  expected loss=0.2730871  P(node) =0.0379
##     class counts:   551   126    54    25     2
##    probabilities: 0.727 0.166 0.071 0.033 0.003 
##   left son=180 (586 obs) right son=181 (172 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=1.4527870, (0 missing)
##       age               < 67.5   to the right, improve=1.2745370, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.1236350, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.8891357, (0 missing)
##       reimbursement2008 < 1125   to the right, improve=0.6899320, (0 missing)
## 
## Node number 91: 13 observations
##   predicted class=B1  expected loss=0.6153846  P(node) =0.00065
##     class counts:     5     3     5     0     0
##    probabilities: 0.385 0.231 0.385 0.000 0.000 
## 
## Node number 92: 713 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.2720898  P(node) =0.03565
##     class counts:   519   125    51    14     4
##    probabilities: 0.728 0.175 0.072 0.020 0.006 
##   left son=184 (691 obs) right son=185 (22 obs)
##   Primary splits:
##       age               < 39.5   to the right, improve=1.1668370, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.1390500, (0 missing)
##       reimbursement2008 < 1465   to the left,  improve=0.9813589, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.5722300, (0 missing)
##       cancer            < 0.5    to the right, improve=0.3196481, (0 missing)
## 
## Node number 93: 58 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4482759  P(node) =0.0029
##     class counts:    32    14     9     3     0
##    probabilities: 0.552 0.241 0.155 0.052 0.000 
##   left son=186 (15 obs) right son=187 (43 obs)
##   Primary splits:
##       age               < 69.5   to the left,  improve=3.2494520, (0 missing)
##       arthritis         < 0.5    to the left,  improve=2.0076310, (0 missing)
##       reimbursement2008 < 1420   to the left,  improve=1.5737930, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7189879, (0 missing)
##       depression        < 0.5    to the right, improve=0.5328407, (0 missing)
## 
## Node number 94: 412 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3058252  P(node) =0.0206
##     class counts:   286    79    34    12     1
##    probabilities: 0.694 0.192 0.083 0.029 0.002 
##   left son=188 (90 obs) right son=189 (322 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=1.7905600, (0 missing)
##       kidney            < 0.5    to the right, improve=1.1304480, (0 missing)
##       reimbursement2008 < 845    to the right, improve=1.0921920, (0 missing)
##       age               < 46.5   to the right, improve=0.8862043, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.6585376, (0 missing)
## 
## Node number 95: 407 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4226044  P(node) =0.02035
##     class counts:   235   107    40    24     1
##    probabilities: 0.577 0.263 0.098 0.059 0.002 
##   left son=190 (382 obs) right son=191 (25 obs)
##   Primary splits:
##       age               < 89.5   to the left,  improve=2.713552, (0 missing)
##       reimbursement2008 < 1175   to the right, improve=1.792258, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.783573, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.289334, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.141444, (0 missing)
## 
## Node number 96: 524 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.3282443  P(node) =0.0262
##     class counts:   352   103    52    16     1
##    probabilities: 0.672 0.197 0.099 0.031 0.002 
##   left son=192 (517 obs) right son=193 (7 obs)
##   Primary splits:
##       age               < 96.5   to the left,  improve=1.6925650, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.3207170, (0 missing)
##       depression        < 0.5    to the left,  improve=1.3189090, (0 missing)
##       copd              < 0.5    to the left,  improve=1.0179070, (0 missing)
##       reimbursement2008 < 2555   to the right, improve=0.9997021, (0 missing)
## 
## Node number 97: 156 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.3974359  P(node) =0.0078
##     class counts:    94    50     7     4     1
##    probabilities: 0.603 0.321 0.045 0.026 0.006 
##   left son=194 (118 obs) right son=195 (38 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=3.3295250, (0 missing)
##       age               < 71.5   to the left,  improve=1.4519230, (0 missing)
##       reimbursement2008 < 2805   to the right, improve=1.4487180, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.1881170, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4811752, (0 missing)
## 
## Node number 98: 110 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.3818182  P(node) =0.0055
##     class counts:    68    26     9     6     1
##    probabilities: 0.618 0.236 0.082 0.055 0.009 
##   left son=196 (32 obs) right son=197 (78 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=1.5659670, (0 missing)
##       reimbursement2008 < 1805   to the right, improve=1.4835180, (0 missing)
##       age               < 65     to the left,  improve=1.0413730, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.8202845, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.5535759, (0 missing)
##   Surrogate splits:
##       copd       < 0.5    to the right, agree=0.727, adj=0.063, (0 split)
##       age        < 87.5   to the right, agree=0.718, adj=0.031, (0 split)
##       alzheimers < 0.5    to the right, agree=0.718, adj=0.031, (0 split)
## 
## Node number 99: 151 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.5430464  P(node) =0.00755
##     class counts:    69    50    28     3     1
##    probabilities: 0.457 0.331 0.185 0.020 0.007 
##   left son=198 (140 obs) right son=199 (11 obs)
##   Primary splits:
##       reimbursement2008 < 1675   to the right, improve=1.6192660, (0 missing)
##       age               < 79.5   to the left,  improve=1.2019600, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.1347180, (0 missing)
##       arthritis         < 0.5    to the right, improve=1.0828460, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.7387061, (0 missing)
## 
## Node number 100: 63 observations
##   predicted class=B1  expected loss=0.3968254  P(node) =0.00315
##     class counts:    38    12     9     4     0
##    probabilities: 0.603 0.190 0.143 0.063 0.000 
## 
## Node number 101: 19 observations
##   predicted class=B2  expected loss=0.4736842  P(node) =0.00095
##     class counts:     6    10     3     0     0
##    probabilities: 0.316 0.526 0.158 0.000 0.000 
## 
## Node number 102: 28 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.0014
##     class counts:     9    16     2     1     0
##    probabilities: 0.321 0.571 0.071 0.036 0.000 
## 
## Node number 103: 36 observations,    complexity param=0.000507048
##   predicted class=B3  expected loss=0.6388889  P(node) =0.0018
##     class counts:     9    12    13     2     0
##    probabilities: 0.250 0.333 0.361 0.056 0.000 
##   left son=206 (10 obs) right son=207 (26 obs)
##   Primary splits:
##       reimbursement2008 < 1990   to the left,  improve=2.3444440, (0 missing)
##       age               < 78.5   to the left,  improve=1.6694440, (0 missing)
##       depression        < 0.5    to the right, improve=1.5277780, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.9801587, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3518519, (0 missing)
## 
## Node number 104: 849 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.459364  P(node) =0.04245
##     class counts:   459   246    92    45     7
##    probabilities: 0.541 0.290 0.108 0.053 0.008 
##   left son=208 (406 obs) right son=209 (443 obs)
##   Primary splits:
##       age               < 73.5   to the right, improve=4.000432, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=3.247702, (0 missing)
##       reimbursement2008 < 1855   to the left,  improve=2.540980, (0 missing)
##       kidney            < 0.5    to the left,  improve=2.518808, (0 missing)
##       copd              < 0.5    to the left,  improve=2.326450, (0 missing)
##   Surrogate splits:
##       osteoporosis      < 0.5    to the right, agree=0.541, adj=0.039, (0 split)
##       reimbursement2008 < 2215   to the right, agree=0.537, adj=0.032, (0 split)
##       heart.failure     < 0.5    to the right, agree=0.527, adj=0.010, (0 split)
## 
## Node number 105: 31 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6451613  P(node) =0.00155
##     class counts:     9    11    10     1     0
##    probabilities: 0.290 0.355 0.323 0.032 0.000 
##   left son=210 (17 obs) right son=211 (14 obs)
##   Primary splits:
##       age               < 75.5   to the right, improve=1.5871510, (0 missing)
##       reimbursement2008 < 2370   to the left,  improve=1.1497190, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5679117, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.5234255, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.3567588, (0 missing)
##   Surrogate splits:
##       osteoporosis      < 0.5    to the left,  agree=0.677, adj=0.286, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.581, adj=0.071, (0 split)
##       kidney            < 0.5    to the left,  agree=0.581, adj=0.071, (0 split)
##       reimbursement2008 < 2035   to the right, agree=0.581, adj=0.071, (0 split)
## 
## Node number 106: 80 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.425  P(node) =0.004
##     class counts:    46    23     5     6     0
##    probabilities: 0.575 0.287 0.062 0.075 0.000 
##   left son=212 (55 obs) right son=213 (25 obs)
##   Primary splits:
##       age               < 93.5   to the left,  improve=2.611364, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.487349, (0 missing)
##       reimbursement2008 < 2125   to the right, improve=1.457423, (0 missing)
##       stroke            < 0.5    to the right, improve=1.369444, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.209632, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.7, adj=0.04, (0 split)
## 
## Node number 107: 315 observations,    complexity param=0.001064801
##   predicted class=B2  expected loss=0.5904762  P(node) =0.01575
##     class counts:   124   129    45    16     1
##    probabilities: 0.394 0.410 0.143 0.051 0.003 
##   left son=214 (298 obs) right son=215 (17 obs)
##   Primary splits:
##       cancer            < 0.5    to the left,  improve=2.959923, (0 missing)
##       age               < 71.5   to the left,  improve=2.862764, (0 missing)
##       reimbursement2008 < 1705   to the left,  improve=2.440816, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.340605, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.203641, (0 missing)
## 
## Node number 108: 317 observations,    complexity param=0.002053544
##   predicted class=B1  expected loss=0.488959  P(node) =0.01585
##     class counts:   162   100    41    12     2
##    probabilities: 0.511 0.315 0.129 0.038 0.006 
##   left son=216 (281 obs) right son=217 (36 obs)
##   Primary splits:
##       cancer            < 0.5    to the left,  improve=7.0540640, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.2948500, (0 missing)
##       age               < 67.5   to the left,  improve=1.1694920, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7114914, (0 missing)
##       reimbursement2008 < 3375   to the right, improve=0.7111587, (0 missing)
## 
## Node number 109: 297 observations,    complexity param=0.001216915
##   predicted class=B2  expected loss=0.6094276  P(node) =0.01485
##     class counts:   103   116    53    25     0
##    probabilities: 0.347 0.391 0.178 0.084 0.000 
##   left son=218 (213 obs) right son=219 (84 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=3.189782, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=2.501684, (0 missing)
##       stroke            < 0.5    to the left,  improve=2.034430, (0 missing)
##       reimbursement2008 < 2545   to the right, improve=1.945862, (0 missing)
##       copd              < 0.5    to the left,  improve=1.405257, (0 missing)
## 
## Node number 110: 174 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5574713  P(node) =0.0087
##     class counts:    54    77    36     6     1
##    probabilities: 0.310 0.443 0.207 0.034 0.006 
##   left son=220 (157 obs) right son=221 (17 obs)
##   Primary splits:
##       reimbursement2008 < 2965   to the left,  improve=2.237107, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.712199, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.626229, (0 missing)
##       age               < 66.5   to the left,  improve=1.521372, (0 missing)
##       copd              < 0.5    to the left,  improve=1.472441, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.948, adj=0.471, (0 split)
## 
## Node number 111: 112 observations,    complexity param=0.000190143
##   predicted class=B2  expected loss=0.3928571  P(node) =0.0056
##     class counts:    25    68    10     8     1
##    probabilities: 0.223 0.607 0.089 0.071 0.009 
##   left son=222 (81 obs) right son=223 (31 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=2.8140400, (0 missing)
##       age               < 88.5   to the left,  improve=1.5837910, (0 missing)
##       reimbursement2008 < 3405   to the left,  improve=1.3337910, (0 missing)
##       copd              < 0.5    to the left,  improve=1.0054300, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.8988095, (0 missing)
## 
## Node number 112: 419 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.4033413  P(node) =0.02095
##     class counts:   250   111    42    13     3
##    probabilities: 0.597 0.265 0.100 0.031 0.007 
##   left son=224 (330 obs) right son=225 (89 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=2.610752, (0 missing)
##       reimbursement2008 < 8430   to the right, improve=2.207527, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.748820, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.716918, (0 missing)
##       copd              < 0.5    to the left,  improve=1.485559, (0 missing)
## 
## Node number 113: 144 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.5763889  P(node) =0.0072
##     class counts:    61    47    29     7     0
##    probabilities: 0.424 0.326 0.201 0.049 0.000 
##   left son=226 (58 obs) right son=227 (86 obs)
##   Primary splits:
##       age               < 73.5   to the left,  improve=2.071126, (0 missing)
##       reimbursement2008 < 3585   to the right, improve=2.059784, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.866475, (0 missing)
##       copd              < 0.5    to the right, improve=1.815446, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.213565, (0 missing)
##   Surrogate splits:
##       ihd               < 0.5    to the left,  agree=0.604, adj=0.017, (0 split)
##       reimbursement2008 < 25970  to the right, agree=0.604, adj=0.017, (0 split)
## 
## Node number 114: 55 observations,    complexity param=0.000760572
##   predicted class=B1  expected loss=0.6181818  P(node) =0.00275
##     class counts:    21    15    12     7     0
##    probabilities: 0.382 0.273 0.218 0.127 0.000 
##   left son=228 (42 obs) right son=229 (13 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=4.3525140, (0 missing)
##       copd              < 0.5    to the left,  improve=1.5063600, (0 missing)
##       reimbursement2008 < 3745   to the left,  improve=1.2449130, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.0678650, (0 missing)
##       age               < 64.5   to the left,  improve=0.7169246, (0 missing)
##   Surrogate splits:
##       age < 94     to the left,  agree=0.782, adj=0.077, (0 split)
## 
## Node number 115: 64 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.546875  P(node) =0.0032
##     class counts:    15    29    14     6     0
##    probabilities: 0.234 0.453 0.219 0.094 0.000 
##   left son=230 (41 obs) right son=231 (23 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.4228860, (0 missing)
##       reimbursement2008 < 9080   to the right, improve=1.9265930, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=1.1557870, (0 missing)
##       age               < 66.5   to the right, improve=1.0320330, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.7558656, (0 missing)
##   Surrogate splits:
##       age               < 61     to the right, agree=0.672, adj=0.087, (0 split)
##       reimbursement2008 < 6480   to the right, agree=0.656, adj=0.043, (0 split)
## 
## Node number 116: 20 observations
##   predicted class=B1  expected loss=0.45  P(node) =0.001
##     class counts:    11     3     6     0     0
##    probabilities: 0.550 0.150 0.300 0.000 0.000 
## 
## Node number 117: 193 observations,    complexity param=0.0008619815
##   predicted class=B2  expected loss=0.5803109  P(node) =0.00965
##     class counts:    64    81    36    12     0
##    probabilities: 0.332 0.420 0.187 0.062 0.000 
##   left son=234 (136 obs) right son=235 (57 obs)
##   Primary splits:
##       age               < 82.5   to the left,  improve=2.821502, (0 missing)
##       cancer            < 0.5    to the left,  improve=2.768983, (0 missing)
##       reimbursement2008 < 8080   to the right, improve=2.356612, (0 missing)
##       bucket2008        < 2.5    to the right, improve=2.356612, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=2.157632, (0 missing)
## 
## Node number 118: 13 observations
##   predicted class=B3  expected loss=0.5384615  P(node) =0.00065
##     class counts:     4     3     6     0     0
##    probabilities: 0.308 0.231 0.462 0.000 0.000 
## 
## Node number 119: 94 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.5425532  P(node) =0.0047
##     class counts:    18    43    24     9     0
##    probabilities: 0.191 0.457 0.255 0.096 0.000 
##   left son=238 (8 obs) right son=239 (86 obs)
##   Primary splits:
##       reimbursement2008 < 17845  to the right, improve=2.4226870, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.0548490, (0 missing)
##       age               < 76.5   to the left,  improve=0.9148936, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.8079343, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7191072, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.968, adj=0.625, (0 split)
## 
## Node number 120: 791 observations,    complexity param=0.0008746577
##   predicted class=B2  expected loss=0.5979772  P(node) =0.03955
##     class counts:   292   318   129    48     4
##    probabilities: 0.369 0.402 0.163 0.061 0.005 
##   left son=240 (277 obs) right son=241 (514 obs)
##   Primary splits:
##       age               < 70.5   to the left,  improve=3.355752, (0 missing)
##       reimbursement2008 < 49845  to the left,  improve=3.229908, (0 missing)
##       ihd               < 0.5    to the left,  improve=2.761119, (0 missing)
##       copd              < 0.5    to the left,  improve=2.003968, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.265923, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 3445   to the left,  agree=0.655, adj=0.014, (0 split)
## 
## Node number 121: 173 observations,    complexity param=0.0005324004
##   predicted class=B2  expected loss=0.566474  P(node) =0.00865
##     class counts:    32    75    53    12     1
##    probabilities: 0.185 0.434 0.306 0.069 0.006 
##   left son=242 (39 obs) right son=243 (134 obs)
##   Primary splits:
##       age               < 82.5   to the right, improve=5.0010880, (0 missing)
##       reimbursement2008 < 6630   to the left,  improve=2.0288640, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.2040470, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.8841145, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8253101, (0 missing)
## 
## Node number 122: 69 observations
##   predicted class=B2  expected loss=0.3188406  P(node) =0.00345
##     class counts:    10    47     9     3     0
##    probabilities: 0.145 0.681 0.130 0.043 0.000 
## 
## Node number 123: 535 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5364486  P(node) =0.02675
##     class counts:   114   248   113    54     6
##    probabilities: 0.213 0.464 0.211 0.101 0.011 
##   left son=246 (282 obs) right son=247 (253 obs)
##   Primary splits:
##       depression   < 0.5    to the left,  improve=2.483857, (0 missing)
##       age          < 34     to the right, improve=2.414565, (0 missing)
##       alzheimers   < 0.5    to the left,  improve=1.680399, (0 missing)
##       osteoporosis < 0.5    to the left,  improve=1.549482, (0 missing)
##       ihd          < 0.5    to the left,  improve=1.112006, (0 missing)
##   Surrogate splits:
##       age               < 63.5   to the right, agree=0.574, adj=0.099, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.574, adj=0.099, (0 split)
##       reimbursement2008 < 8115   to the left,  agree=0.574, adj=0.099, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.568, adj=0.087, (0 split)
##       stroke            < 0.5    to the left,  agree=0.536, adj=0.020, (0 split)
## 
## Node number 124: 638 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.630094  P(node) =0.0319
##     class counts:   139   236   154    93    16
##    probabilities: 0.218 0.370 0.241 0.146 0.025 
##   left son=248 (612 obs) right son=249 (26 obs)
##   Primary splits:
##       age               < 44.5   to the right, improve=4.240890, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.955476, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.928245, (0 missing)
##       reimbursement2008 < 6575   to the right, improve=1.687162, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.121735, (0 missing)
## 
## Node number 125: 452 observations,    complexity param=0.0002028192
##   predicted class=B2  expected loss=0.4977876  P(node) =0.0226
##     class counts:    56   227   107    55     7
##    probabilities: 0.124 0.502 0.237 0.122 0.015 
##   left son=250 (143 obs) right son=251 (309 obs)
##   Primary splits:
##       reimbursement2008 < 5300   to the left,  improve=3.3421300, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.7850810, (0 missing)
##       age               < 39     to the left,  improve=1.2021390, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.9484846, (0 missing)
##       copd              < 0.5    to the left,  improve=0.7242827, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.715, adj=0.098, (0 split)
##       age        < 99.5   to the right, agree=0.686, adj=0.007, (0 split)
## 
## Node number 126: 53 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6603774  P(node) =0.00265
##     class counts:    16    18     4    14     1
##    probabilities: 0.302 0.340 0.075 0.264 0.019 
##   left son=252 (20 obs) right son=253 (33 obs)
##   Primary splits:
##       reimbursement2008 < 25800  to the right, improve=2.686221, (0 missing)
##       stroke            < 0.5    to the right, improve=1.745810, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.708468, (0 missing)
##       cancer            < 0.5    to the right, improve=1.513346, (0 missing)
##       copd              < 0.5    to the right, improve=1.510950, (0 missing)
##   Surrogate splits:
##       bucket2008    < 4.5    to the right, agree=0.679, adj=0.15, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.660, adj=0.10, (0 split)
## 
## Node number 127: 883 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6375991  P(node) =0.04415
##     class counts:   103   320   203   215    42
##    probabilities: 0.117 0.362 0.230 0.243 0.048 
##   left son=254 (396 obs) right son=255 (487 obs)
##   Primary splits:
##       reimbursement2008 < 26375  to the left,  improve=3.823201, (0 missing)
##       age               < 65.5   to the right, improve=2.689667, (0 missing)
##       copd              < 0.5    to the left,  improve=1.850928, (0 missing)
##       depression        < 0.5    to the left,  improve=1.564142, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=1.541530, (0 missing)
##   Surrogate splits:
##       bucket2008    < 3.5    to the left,  agree=0.736, adj=0.412, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.576, adj=0.056, (0 split)
##       copd          < 0.5    to the left,  agree=0.564, adj=0.028, (0 split)
## 
## Node number 160: 1586 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1431274  P(node) =0.0793
##     class counts:  1359   137    68    19     3
##    probabilities: 0.857 0.086 0.043 0.012 0.002 
##   left son=320 (756 obs) right son=321 (830 obs)
##   Primary splits:
##       age               < 71.5   to the left,  improve=0.9232109, (0 missing)
##       reimbursement2008 < 665    to the left,  improve=0.6940889, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6379602, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.5784235, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5106421, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 655    to the right, agree=0.530, adj=0.015, (0 split)
##       depression        < 0.5    to the right, agree=0.529, adj=0.012, (0 split)
##       copd              < 0.5    to the right, agree=0.528, adj=0.011, (0 split)
##       stroke            < 0.5    to the right, agree=0.524, adj=0.001, (0 split)
## 
## Node number 161: 178 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1966292  P(node) =0.0089
##     class counts:   143    25     7     3     0
##    probabilities: 0.803 0.140 0.039 0.017 0.000 
##   left son=322 (171 obs) right son=323 (7 obs)
##   Primary splits:
##       reimbursement2008 < 225    to the right, improve=2.3903390, (0 missing)
##       age               < 79.5   to the right, improve=0.6636044, (0 missing)
##       depression        < 0.5    to the right, improve=0.6166862, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.1555824, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.1467316, (0 missing)
## 
## Node number 170: 19 observations
##   predicted class=B1  expected loss=0.2631579  P(node) =0.00095
##     class counts:    14     2     1     2     0
##    probabilities: 0.737 0.105 0.053 0.105 0.000 
## 
## Node number 171: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     2     2     3     0     0
##    probabilities: 0.286 0.286 0.429 0.000 0.000 
## 
## Node number 176: 544 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1930147  P(node) =0.0272
##     class counts:   439    60    26    17     2
##    probabilities: 0.807 0.110 0.048 0.031 0.004 
##   left son=352 (338 obs) right son=353 (206 obs)
##   Primary splits:
##       reimbursement2008 < 905    to the left,  improve=1.0110110, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.9330888, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6888143, (0 missing)
##       age               < 83.5   to the left,  improve=0.6468196, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.4582147, (0 missing)
##   Surrogate splits:
##       age    < 97.5   to the left,  agree=0.629, adj=0.019, (0 split)
##       cancer < 0.5    to the left,  agree=0.627, adj=0.015, (0 split)
##       copd   < 0.5    to the left,  agree=0.623, adj=0.005, (0 split)
## 
## Node number 177: 267 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2397004  P(node) =0.01335
##     class counts:   203    45    12     7     0
##    probabilities: 0.760 0.169 0.045 0.026 0.000 
##   left son=354 (182 obs) right son=355 (85 obs)
##   Primary splits:
##       reimbursement2008 < 795    to the right, improve=1.3274960, (0 missing)
##       age               < 71.5   to the left,  improve=0.8090960, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6076067, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.4599499, (0 missing)
##       cancer            < 0.5    to the right, improve=0.4324521, (0 missing)
## 
## Node number 178: 133 observations
##   predicted class=B1  expected loss=0.2631579  P(node) =0.00665
##     class counts:    98    24     9     1     1
##    probabilities: 0.737 0.180 0.068 0.008 0.008 
## 
## Node number 179: 7 observations
##   predicted class=B2  expected loss=0.5714286  P(node) =0.00035
##     class counts:     2     3     1     1     0
##    probabilities: 0.286 0.429 0.143 0.143 0.000 
## 
## Node number 180: 586 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.2559727  P(node) =0.0293
##     class counts:   436    88    43    19     0
##    probabilities: 0.744 0.150 0.073 0.032 0.000 
##   left son=360 (449 obs) right son=361 (137 obs)
##   Primary splits:
##       age               < 67.5   to the right, improve=1.7267490, (0 missing)
##       copd              < 0.5    to the left,  improve=1.0095940, (0 missing)
##       reimbursement2008 < 1235   to the left,  improve=0.9296137, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.4946966, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.4469803, (0 missing)
## 
## Node number 181: 172 observations,    complexity param=0.0001303838
##   predicted class=B1  expected loss=0.3313953  P(node) =0.0086
##     class counts:   115    38    11     6     2
##    probabilities: 0.669 0.221 0.064 0.035 0.012 
##   left son=362 (143 obs) right son=363 (29 obs)
##   Primary splits:
##       age               < 83.5   to the left,  improve=1.8398370, (0 missing)
##       reimbursement2008 < 1115   to the right, improve=1.5955310, (0 missing)
##       copd              < 0.5    to the right, improve=1.1082360, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.0821000, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.9757667, (0 missing)
## 
## Node number 184: 691 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.2662808  P(node) =0.03455
##     class counts:   507   119    50    13     2
##    probabilities: 0.734 0.172 0.072 0.019 0.003 
##   left son=368 (628 obs) right son=369 (63 obs)
##   Primary splits:
##       reimbursement2008 < 1465   to the left,  improve=1.0827960, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8965233, (0 missing)
##       age               < 50     to the left,  improve=0.7515753, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.5491404, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.4331673, (0 missing)
## 
## Node number 185: 22 observations
##   predicted class=B1  expected loss=0.4545455  P(node) =0.0011
##     class counts:    12     6     1     1     2
##    probabilities: 0.545 0.273 0.045 0.045 0.091 
## 
## Node number 186: 15 observations
##   predicted class=B1  expected loss=0.1333333  P(node) =0.00075
##     class counts:    13     0     2     0     0
##    probabilities: 0.867 0.000 0.133 0.000 0.000 
## 
## Node number 187: 43 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5581395  P(node) =0.00215
##     class counts:    19    14     7     3     0
##    probabilities: 0.442 0.326 0.163 0.070 0.000 
##   left son=374 (35 obs) right son=375 (8 obs)
##   Primary splits:
##       reimbursement2008 < 1355   to the left,  improve=1.9905320, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.3960870, (0 missing)
##       age               < 78.5   to the left,  improve=0.5397797, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4476744, (0 missing)
##       depression        < 0.5    to the right, improve=0.3331424, (0 missing)
##   Surrogate splits:
##       arthritis < 0.5    to the left,  agree=0.837, adj=0.125, (0 split)
## 
## Node number 188: 90 observations
##   predicted class=B1  expected loss=0.2111111  P(node) =0.0045
##     class counts:    71    10     7     2     0
##    probabilities: 0.789 0.111 0.078 0.022 0.000 
## 
## Node number 189: 322 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3322981  P(node) =0.0161
##     class counts:   215    69    27    10     1
##    probabilities: 0.668 0.214 0.084 0.031 0.003 
##   left son=378 (310 obs) right son=379 (12 obs)
##   Primary splits:
##       age               < 46.5   to the right, improve=1.9484870, (0 missing)
##       reimbursement2008 < 1135   to the right, improve=1.2465950, (0 missing)
##       kidney            < 0.5    to the right, improve=0.8858863, (0 missing)
##       copd              < 0.5    to the right, improve=0.5966936, (0 missing)
##       depression        < 0.5    to the left,  improve=0.3370662, (0 missing)
## 
## Node number 190: 382 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4057592  P(node) =0.0191
##     class counts:   227    96    36    22     1
##    probabilities: 0.594 0.251 0.094 0.058 0.003 
##   left son=380 (352 obs) right son=381 (30 obs)
##   Primary splits:
##       reimbursement2008 < 1175   to the right, improve=1.447781, (0 missing)
##       arthritis         < 0.5    to the right, improve=1.260633, (0 missing)
##       depression        < 0.5    to the left,  improve=1.219881, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.175814, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.149973, (0 missing)
## 
## Node number 191: 25 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.56  P(node) =0.00125
##     class counts:     8    11     4     2     0
##    probabilities: 0.320 0.440 0.160 0.080 0.000 
##   left son=382 (7 obs) right son=383 (18 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=2.4349210, (0 missing)
##       age               < 94.5   to the left,  improve=1.3873020, (0 missing)
##       reimbursement2008 < 1490   to the right, improve=0.5936508, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.3138889, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1515   to the right, agree=0.84, adj=0.429, (0 split)
##       osteoporosis      < 0.5    to the right, agree=0.76, adj=0.143, (0 split)
## 
## Node number 192: 517 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3230174  P(node) =0.02585
##     class counts:   350   100    50    16     1
##    probabilities: 0.677 0.193 0.097 0.031 0.002 
##   left son=384 (395 obs) right son=385 (122 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=1.3507060, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.1170580, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9771406, (0 missing)
##       reimbursement2008 < 2555   to the right, improve=0.9492119, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.9266289, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1575   to the right, agree=0.766, adj=0.008, (0 split)
## 
## Node number 193: 7 observations
##   predicted class=B2  expected loss=0.5714286  P(node) =0.00035
##     class counts:     2     3     2     0     0
##    probabilities: 0.286 0.429 0.286 0.000 0.000 
## 
## Node number 194: 118 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.3389831  P(node) =0.0059
##     class counts:    78    31     6     2     1
##    probabilities: 0.661 0.263 0.051 0.017 0.008 
##   left son=388 (45 obs) right son=389 (73 obs)
##   Primary splits:
##       age               < 69.5   to the left,  improve=1.1850730, (0 missing)
##       reimbursement2008 < 3390   to the left,  improve=0.8082435, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4190278, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3093904, (0 missing)
##       cancer            < 0.5    to the right, improve=0.2861896, (0 missing)
##   Surrogate splits:
##       alzheimers < 0.5    to the right, agree=0.653, adj=0.089, (0 split)
##       stroke     < 0.5    to the right, agree=0.636, adj=0.044, (0 split)
## 
## Node number 195: 38 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5  P(node) =0.0019
##     class counts:    16    19     1     2     0
##    probabilities: 0.421 0.500 0.026 0.053 0.000 
##   left son=390 (12 obs) right son=391 (26 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=2.1828610, (0 missing)
##       age               < 82     to the right, improve=1.6698930, (0 missing)
##       reimbursement2008 < 2825   to the right, improve=0.6842105, (0 missing)
##       depression        < 0.5    to the right, improve=0.5608097, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5361943, (0 missing)
##   Surrogate splits:
##       age < 82     to the right, agree=0.763, adj=0.25, (0 split)
## 
## Node number 196: 32 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.0016
##     class counts:    24     4     4     0     0
##    probabilities: 0.750 0.125 0.125 0.000 0.000 
## 
## Node number 197: 78 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.4358974  P(node) =0.0039
##     class counts:    44    22     5     6     1
##    probabilities: 0.564 0.282 0.064 0.077 0.013 
##   left son=394 (20 obs) right son=395 (58 obs)
##   Primary splits:
##       reimbursement2008 < 2685   to the right, improve=1.5277630, (0 missing)
##       age               < 65     to the left,  improve=0.8171683, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7077891, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.4080586, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3333333, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the right, agree=0.846, adj=0.40, (0 split)
##       age        < 59.5   to the left,  agree=0.756, adj=0.05, (0 split)
## 
## Node number 198: 140 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5285714  P(node) =0.007
##     class counts:    66    43    27     3     1
##    probabilities: 0.471 0.307 0.193 0.021 0.007 
##   left son=396 (10 obs) right son=397 (130 obs)
##   Primary splits:
##       reimbursement2008 < 1775   to the left,  improve=1.7076920, (0 missing)
##       age               < 79.5   to the left,  improve=1.3659860, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.3345480, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.9142857, (0 missing)
##       cancer            < 0.5    to the right, improve=0.8461408, (0 missing)
## 
## Node number 199: 11 observations
##   predicted class=B2  expected loss=0.3636364  P(node) =0.00055
##     class counts:     3     7     1     0     0
##    probabilities: 0.273 0.636 0.091 0.000 0.000 
## 
## Node number 206: 10 observations
##   predicted class=B1  expected loss=0.4  P(node) =0.0005
##     class counts:     6     2     2     0     0
##    probabilities: 0.600 0.200 0.200 0.000 0.000 
## 
## Node number 207: 26 observations,    complexity param=0.000507048
##   predicted class=B3  expected loss=0.5769231  P(node) =0.0013
##     class counts:     3    10    11     2     0
##    probabilities: 0.115 0.385 0.423 0.077 0.000 
##   left son=414 (12 obs) right son=415 (14 obs)
##   Primary splits:
##       age               < 78.5   to the left,  improve=2.4047620, (0 missing)
##       depression        < 0.5    to the right, improve=1.7636360, (0 missing)
##       reimbursement2008 < 2405   to the left,  improve=1.4060150, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.0902260, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.4722222, (0 missing)
##   Surrogate splits:
##       arthritis         < 0.5    to the right, agree=0.692, adj=0.333, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.654, adj=0.250, (0 split)
##       cancer            < 0.5    to the right, agree=0.615, adj=0.167, (0 split)
##       diabetes          < 0.5    to the left,  agree=0.615, adj=0.167, (0 split)
##       reimbursement2008 < 2455   to the left,  agree=0.615, adj=0.167, (0 split)
## 
## Node number 208: 406 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.3990148  P(node) =0.0203
##     class counts:   244   105    35    19     3
##    probabilities: 0.601 0.259 0.086 0.047 0.007 
##   left son=416 (307 obs) right son=417 (99 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=1.7269200, (0 missing)
##       age               < 88.5   to the left,  improve=1.5011960, (0 missing)
##       reimbursement2008 < 2465   to the right, improve=1.4952500, (0 missing)
##       cancer            < 0.5    to the right, improve=1.0503980, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8595577, (0 missing)
## 
## Node number 209: 443 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.5146727  P(node) =0.02215
##     class counts:   215   141    57    26     4
##    probabilities: 0.485 0.318 0.129 0.059 0.009 
##   left son=418 (261 obs) right son=419 (182 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=4.055554, (0 missing)
##       diabetes          < 0.5    to the left,  improve=3.280522, (0 missing)
##       kidney            < 0.5    to the left,  improve=2.279095, (0 missing)
##       reimbursement2008 < 1775   to the left,  improve=2.187851, (0 missing)
##       copd              < 0.5    to the left,  improve=2.085109, (0 missing)
##   Surrogate splits:
##       kidney < 0.5    to the left,  agree=0.619, adj=0.071, (0 split)
##       copd   < 0.5    to the left,  agree=0.600, adj=0.027, (0 split)
##       age    < 38.5   to the right, agree=0.596, adj=0.016, (0 split)
## 
## Node number 210: 17 observations
##   predicted class=B2  expected loss=0.4705882  P(node) =0.00085
##     class counts:     4     9     4     0     0
##    probabilities: 0.235 0.529 0.235 0.000 0.000 
## 
## Node number 211: 14 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.0007
##     class counts:     5     2     6     1     0
##    probabilities: 0.357 0.143 0.429 0.071 0.000 
## 
## Node number 212: 55 observations
##   predicted class=B1  expected loss=0.3272727  P(node) =0.00275
##     class counts:    37    12     3     3     0
##    probabilities: 0.673 0.218 0.055 0.055 0.000 
## 
## Node number 213: 25 observations,    complexity param=0.000380286
##   predicted class=B2  expected loss=0.56  P(node) =0.00125
##     class counts:     9    11     2     3     0
##    probabilities: 0.360 0.440 0.080 0.120 0.000 
##   left son=426 (15 obs) right son=427 (10 obs)
##   Primary splits:
##       age               < 97.5   to the right, improve=1.6666670, (0 missing)
##       reimbursement2008 < 1995   to the right, improve=0.5153846, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1179487, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.1179487, (0 missing)
##       kidney            < 0.5    to the right, improve=0.1142857, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1685   to the right, agree=0.68, adj=0.2, (0 split)
## 
## Node number 214: 298 observations,    complexity param=0.001064801
##   predicted class=B1  expected loss=0.590604  P(node) =0.0149
##     class counts:   122   117    43    15     1
##    probabilities: 0.409 0.393 0.144 0.050 0.003 
##   left son=428 (162 obs) right son=429 (136 obs)
##   Primary splits:
##       age               < 71.5   to the left,  improve=3.1447400, (0 missing)
##       reimbursement2008 < 1760   to the left,  improve=2.8458740, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9979622, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7325015, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.4523398, (0 missing)
##   Surrogate splits:
##       stroke            < 0.5    to the left,  agree=0.550, adj=0.015, (0 split)
##       reimbursement2008 < 2495   to the left,  agree=0.550, adj=0.015, (0 split)
##       diabetes          < 0.5    to the right, agree=0.547, adj=0.007, (0 split)
## 
## Node number 215: 17 observations
##   predicted class=B2  expected loss=0.2941176  P(node) =0.00085
##     class counts:     2    12     2     1     0
##    probabilities: 0.118 0.706 0.118 0.059 0.000 
## 
## Node number 216: 281 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.4519573  P(node) =0.01405
##     class counts:   154    78    35    12     2
##    probabilities: 0.548 0.278 0.125 0.043 0.007 
##   left son=432 (68 obs) right son=433 (213 obs)
##   Primary splits:
##       age               < 67.5   to the left,  improve=1.4795500, (0 missing)
##       reimbursement2008 < 2995   to the right, improve=1.3998900, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.3998900, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.8817733, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6232495, (0 missing)
## 
## Node number 217: 36 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.3888889  P(node) =0.0018
##     class counts:     8    22     6     0     0
##    probabilities: 0.222 0.611 0.167 0.000 0.000 
##   left son=434 (10 obs) right son=435 (26 obs)
##   Primary splits:
##       reimbursement2008 < 2770   to the left,  improve=2.4239320, (0 missing)
##       age               < 77.5   to the left,  improve=1.1944440, (0 missing)
##       depression        < 0.5    to the left,  improve=1.0277780, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.9725830, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.9470085, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.778, adj=0.2, (0 split)
##       age        < 62.5   to the left,  agree=0.750, adj=0.1, (0 split)
## 
## Node number 218: 213 observations,    complexity param=0.000760572
##   predicted class=B1  expected loss=0.6103286  P(node) =0.01065
##     class counts:    83    75    33    22     0
##    probabilities: 0.390 0.352 0.155 0.103 0.000 
##   left son=436 (146 obs) right son=437 (67 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=2.4874440, (0 missing)
##       reimbursement2008 < 3335   to the right, improve=1.9134220, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.5529040, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.9344707, (0 missing)
##       copd              < 0.5    to the left,  improve=0.7994731, (0 missing)
##   Surrogate splits:
##       age < 35     to the right, agree=0.69, adj=0.015, (0 split)
## 
## Node number 219: 84 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.5119048  P(node) =0.0042
##     class counts:    20    41    20     3     0
##    probabilities: 0.238 0.488 0.238 0.036 0.000 
##   left son=438 (57 obs) right son=439 (27 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=1.5891120, (0 missing)
##       reimbursement2008 < 2735   to the right, improve=1.5503000, (0 missing)
##       age               < 70.5   to the right, improve=0.6885269, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.6357352, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4006211, (0 missing)
##   Surrogate splits:
##       age               < 91.5   to the left,  agree=0.726, adj=0.148, (0 split)
##       reimbursement2008 < 3415   to the left,  agree=0.702, adj=0.074, (0 split)
##       diabetes          < 0.5    to the right, agree=0.690, adj=0.037, (0 split)
## 
## Node number 220: 157 observations,    complexity param=0.0002788764
##   predicted class=B2  expected loss=0.5350318  P(node) =0.00785
##     class counts:    50    73    28     5     1
##    probabilities: 0.318 0.465 0.178 0.032 0.006 
##   left son=440 (150 obs) right son=441 (7 obs)
##   Primary splits:
##       stroke            < 0.5    to the left,  improve=1.886903, (0 missing)
##       copd              < 0.5    to the left,  improve=1.391085, (0 missing)
##       age               < 89.5   to the left,  improve=1.341972, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.236864, (0 missing)
##       reimbursement2008 < 2575   to the right, improve=1.066105, (0 missing)
## 
## Node number 221: 17 observations
##   predicted class=B3  expected loss=0.5294118  P(node) =0.00085
##     class counts:     4     4     8     1     0
##    probabilities: 0.235 0.235 0.471 0.059 0.000 
## 
## Node number 222: 81 observations,    complexity param=0.000190143
##   predicted class=B2  expected loss=0.4691358  P(node) =0.00405
##     class counts:    23    43     8     6     1
##    probabilities: 0.284 0.531 0.099 0.074 0.012 
##   left son=444 (70 obs) right son=445 (11 obs)
##   Primary splits:
##       reimbursement2008 < 3075   to the right, improve=1.2392180, (0 missing)
##       copd              < 0.5    to the left,  improve=1.1799880, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.9098037, (0 missing)
##       age               < 88.5   to the right, improve=0.6730540, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.3344166, (0 missing)
## 
## Node number 223: 31 observations
##   predicted class=B2  expected loss=0.1935484  P(node) =0.00155
##     class counts:     2    25     2     2     0
##    probabilities: 0.065 0.806 0.065 0.065 0.000 
## 
## Node number 224: 330 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.3787879  P(node) =0.0165
##     class counts:   205    77    36    10     2
##    probabilities: 0.621 0.233 0.109 0.030 0.006 
##   left son=448 (120 obs) right son=449 (210 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=3.020996, (0 missing)
##       reimbursement2008 < 7060   to the right, improve=2.104329, (0 missing)
##       age               < 59.5   to the right, improve=1.322458, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.319301, (0 missing)
##       copd              < 0.5    to the left,  improve=1.189474, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4060   to the left,  agree=0.652, adj=0.042, (0 split)
##       age               < 33.5   to the left,  agree=0.645, adj=0.025, (0 split)
## 
## Node number 225: 89 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.494382  P(node) =0.00445
##     class counts:    45    34     6     3     1
##    probabilities: 0.506 0.382 0.067 0.034 0.011 
##   left son=450 (15 obs) right son=451 (74 obs)
##   Primary splits:
##       reimbursement2008 < 12275  to the right, improve=3.3794110, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.9367485, (0 missing)
##       age               < 84.5   to the left,  improve=0.9235279, (0 missing)
##       ihd               < 0.5    to the right, improve=0.5528036, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5281343, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.921, adj=0.533, (0 split)
## 
## Node number 226: 58 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.4655172  P(node) =0.0029
##     class counts:    31    15     8     4     0
##    probabilities: 0.534 0.259 0.138 0.069 0.000 
##   left son=452 (27 obs) right son=453 (31 obs)
##   Primary splits:
##       reimbursement2008 < 6600   to the right, improve=2.6670370, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.9714330, (0 missing)
##       age               < 52.5   to the right, improve=1.1824140, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.9855451, (0 missing)
##       copd              < 0.5    to the right, improve=0.6557471, (0 missing)
##   Surrogate splits:
##       bucket2008    < 2.5    to the right, agree=0.948, adj=0.889, (0 split)
##       alzheimers    < 0.5    to the right, agree=0.655, adj=0.259, (0 split)
##       copd          < 0.5    to the right, agree=0.603, adj=0.148, (0 split)
##       heart.failure < 0.5    to the right, agree=0.603, adj=0.148, (0 split)
##       age           < 59     to the right, agree=0.586, adj=0.111, (0 split)
## 
## Node number 227: 86 observations,    complexity param=0.0003549336
##   predicted class=B2  expected loss=0.627907  P(node) =0.0043
##     class counts:    30    32    21     3     0
##    probabilities: 0.349 0.372 0.244 0.035 0.000 
##   left son=454 (14 obs) right son=455 (72 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=1.4390000, (0 missing)
##       copd              < 0.5    to the right, improve=1.2671440, (0 missing)
##       age               < 81.5   to the right, improve=1.2282230, (0 missing)
##       reimbursement2008 < 4375   to the left,  improve=0.9141660, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.6448968, (0 missing)
## 
## Node number 228: 42 observations,    complexity param=0.000760572
##   predicted class=B1  expected loss=0.5714286  P(node) =0.0021
##     class counts:    18    15     4     5     0
##    probabilities: 0.429 0.357 0.095 0.119 0.000 
##   left son=456 (10 obs) right son=457 (32 obs)
##   Primary splits:
##       reimbursement2008 < 3950   to the left,  improve=2.4148810, (0 missing)
##       copd              < 0.5    to the left,  improve=1.5594190, (0 missing)
##       age               < 64.5   to the left,  improve=1.4964990, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.1023810, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7069264, (0 missing)
## 
## Node number 229: 13 observations
##   predicted class=B3  expected loss=0.3846154  P(node) =0.00065
##     class counts:     3     0     8     2     0
##    probabilities: 0.231 0.000 0.615 0.154 0.000 
## 
## Node number 230: 41 observations
##   predicted class=B2  expected loss=0.4390244  P(node) =0.00205
##     class counts:     9    23     5     4     0
##    probabilities: 0.220 0.561 0.122 0.098 0.000 
## 
## Node number 231: 23 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.6086957  P(node) =0.00115
##     class counts:     6     6     9     2     0
##    probabilities: 0.261 0.261 0.391 0.087 0.000 
##   left son=462 (12 obs) right son=463 (11 obs)
##   Primary splits:
##       reimbursement2008 < 9740   to the right, improve=1.4920950, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.0489130, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.9011858, (0 missing)
##       age               < 82.5   to the right, improve=0.4774845, (0 missing)
##       kidney            < 0.5    to the right, improve=0.2572464, (0 missing)
##   Surrogate splits:
##       age        < 73.5   to the left,  agree=0.783, adj=0.545, (0 split)
##       bucket2008 < 2.5    to the right, agree=0.783, adj=0.545, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.652, adj=0.273, (0 split)
##       arthritis  < 0.5    to the left,  agree=0.652, adj=0.273, (0 split)
##       stroke     < 0.5    to the right, agree=0.565, adj=0.091, (0 split)
## 
## Node number 234: 136 observations,    complexity param=0.0006084576
##   predicted class=B2  expected loss=0.5147059  P(node) =0.0068
##     class counts:    40    66    23     7     0
##    probabilities: 0.294 0.485 0.169 0.051 0.000 
##   left son=468 (72 obs) right son=469 (64 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=2.205882, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=2.001349, (0 missing)
##       reimbursement2008 < 3710   to the left,  improve=1.407495, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.335690, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.307073, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 7755   to the left,  agree=0.574, adj=0.094, (0 split)
##       arthritis         < 0.5    to the right, agree=0.566, adj=0.078, (0 split)
##       bucket2008        < 3.5    to the left,  agree=0.559, adj=0.063, (0 split)
##       age               < 70.5   to the left,  agree=0.551, adj=0.047, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.551, adj=0.047, (0 split)
## 
## Node number 235: 57 observations,    complexity param=0.0006084576
##   predicted class=B1  expected loss=0.5789474  P(node) =0.00285
##     class counts:    24    15    13     5     0
##    probabilities: 0.421 0.263 0.228 0.088 0.000 
##   left son=470 (46 obs) right son=471 (11 obs)
##   Primary splits:
##       cancer            < 0.5    to the left,  improve=1.998405, (0 missing)
##       reimbursement2008 < 7955   to the right, improve=1.956558, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.956558, (0 missing)
##       age               < 91.5   to the right, improve=1.915288, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.477193, (0 missing)
## 
## Node number 238: 8 observations
##   predicted class=B2  expected loss=0.125  P(node) =0.0004
##     class counts:     0     7     0     1     0
##    probabilities: 0.000 0.875 0.000 0.125 0.000 
## 
## Node number 239: 86 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.5813953  P(node) =0.0043
##     class counts:    18    36    24     8     0
##    probabilities: 0.209 0.419 0.279 0.093 0.000 
##   left son=478 (79 obs) right son=479 (7 obs)
##   Primary splits:
##       reimbursement2008 < 15470  to the left,  improve=1.3701160, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.1865130, (0 missing)
##       age               < 75.5   to the left,  improve=0.7490688, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7421039, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.6663848, (0 missing)
## 
## Node number 240: 277 observations,    complexity param=0.0008746577
##   predicted class=B1  expected loss=0.5884477  P(node) =0.01385
##     class counts:   114    91    52    19     1
##    probabilities: 0.412 0.329 0.188 0.069 0.004 
##   left son=480 (199 obs) right son=481 (78 obs)
##   Primary splits:
##       reimbursement2008 < 8845   to the left,  improve=3.810926, (0 missing)
##       copd              < 0.5    to the left,  improve=3.392896, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=2.186722, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.961790, (0 missing)
##       age               < 65.5   to the right, improve=1.441728, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.953, adj=0.833, (0 split)
##       age        < 29.5   to the right, agree=0.722, adj=0.013, (0 split)
## 
## Node number 241: 514 observations,    complexity param=0.0008746577
##   predicted class=B2  expected loss=0.5583658  P(node) =0.0257
##     class counts:   178   227    77    29     3
##    probabilities: 0.346 0.442 0.150 0.056 0.006 
##   left son=482 (327 obs) right son=483 (187 obs)
##   Primary splits:
##       reimbursement2008 < 5045   to the right, improve=4.8841090, (0 missing)
##       age               < 77.5   to the left,  improve=3.3027050, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.9008760, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.9763248, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7270267, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.722, adj=0.235, (0 split)
## 
## Node number 242: 39 observations
##   predicted class=B2  expected loss=0.3076923  P(node) =0.00195
##     class counts:     4    27     6     1     1
##    probabilities: 0.103 0.692 0.154 0.026 0.026 
## 
## Node number 243: 134 observations,    complexity param=0.0005324004
##   predicted class=B2  expected loss=0.641791  P(node) =0.0067
##     class counts:    28    48    47    11     0
##    probabilities: 0.209 0.358 0.351 0.082 0.000 
##   left son=486 (120 obs) right son=487 (14 obs)
##   Primary splits:
##       age               < 55     to the right, improve=2.1647830, (0 missing)
##       reimbursement2008 < 6810   to the left,  improve=1.9339560, (0 missing)
##       depression        < 0.5    to the left,  improve=1.6866340, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.1492540, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.6824682, (0 missing)
## 
## Node number 246: 282 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5283688  P(node) =0.0141
##     class counts:    68   133    44    33     4
##    probabilities: 0.241 0.472 0.156 0.117 0.014 
##   left son=492 (183 obs) right son=493 (99 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=1.953103, (0 missing)
##       age               < 79.5   to the right, improve=1.706579, (0 missing)
##       copd              < 0.5    to the left,  improve=1.416467, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.155080, (0 missing)
##       reimbursement2008 < 3985   to the left,  improve=1.070900, (0 missing)
## 
## Node number 247: 253 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5454545  P(node) =0.01265
##     class counts:    46   115    69    21     2
##    probabilities: 0.182 0.455 0.273 0.083 0.008 
##   left son=494 (241 obs) right son=495 (12 obs)
##   Primary splits:
##       age               < 40.5   to the right, improve=1.7374600, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.3259550, (0 missing)
##       reimbursement2008 < 27370  to the left,  improve=1.2197450, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.9664812, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8621215, (0 missing)
## 
## Node number 248: 612 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.625817  P(node) =0.0306
##     class counts:   138   229   139    90    16
##    probabilities: 0.225 0.374 0.227 0.147 0.026 
##   left son=496 (346 obs) right son=497 (266 obs)
##   Primary splits:
##       reimbursement2008 < 6575   to the right, improve=1.895835, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.891624, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.621569, (0 missing)
##       age               < 79.5   to the right, improve=1.437351, (0 missing)
##       depression        < 0.5    to the left,  improve=1.158424, (0 missing)
##   Surrogate splits:
##       bucket2008    < 2.5    to the right, agree=0.884, adj=0.733, (0 split)
##       heart.failure < 0.5    to the right, agree=0.592, adj=0.060, (0 split)
##       ihd           < 0.5    to the right, agree=0.585, adj=0.045, (0 split)
##       age           < 97.5   to the left,  agree=0.574, adj=0.019, (0 split)
## 
## Node number 249: 26 observations,    complexity param=0.0001521144
##   predicted class=B3  expected loss=0.4230769  P(node) =0.0013
##     class counts:     1     7    15     3     0
##    probabilities: 0.038 0.269 0.577 0.115 0.000 
##   left son=498 (7 obs) right son=499 (19 obs)
##   Primary splits:
##       age               < 34     to the left,  improve=1.2272990, (0 missing)
##       reimbursement2008 < 9145   to the left,  improve=0.7893414, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.6847662, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.4615385, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.3738928, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 12030  to the right, agree=0.808, adj=0.286, (0 split)
## 
## Node number 250: 143 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.4055944  P(node) =0.00715
##     class counts:    20    85    22    15     1
##    probabilities: 0.140 0.594 0.154 0.105 0.007 
##   left son=500 (11 obs) right son=501 (132 obs)
##   Primary splits:
##       reimbursement2008 < 5155   to the right, improve=1.6981350, (0 missing)
##       age               < 81.5   to the right, improve=1.1198620, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.6517483, (0 missing)
##       cancer            < 0.5    to the right, improve=0.5239179, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5030303, (0 missing)
## 
## Node number 251: 309 observations,    complexity param=0.0002028192
##   predicted class=B2  expected loss=0.5404531  P(node) =0.01545
##     class counts:    36   142    85    40     6
##    probabilities: 0.117 0.460 0.275 0.129 0.019 
##   left son=502 (24 obs) right son=503 (285 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=1.6851900, (0 missing)
##       age               < 95.5   to the right, improve=1.5390930, (0 missing)
##       depression        < 0.5    to the right, improve=0.9172647, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8659759, (0 missing)
##       reimbursement2008 < 5385   to the right, improve=0.7334569, (0 missing)
## 
## Node number 252: 20 observations,    complexity param=0.0004563432
##   predicted class=B1  expected loss=0.45  P(node) =0.001
##     class counts:    11     5     1     3     0
##    probabilities: 0.550 0.250 0.050 0.150 0.000 
##   left son=504 (11 obs) right son=505 (9 obs)
##   Primary splits:
##       age               < 79.5   to the left,  improve=3.4121210, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.1890110, (0 missing)
##       reimbursement2008 < 40870  to the left,  improve=0.3978022, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1166667, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 41445  to the left,  agree=0.65, adj=0.222, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.60, adj=0.111, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.60, adj=0.111, (0 split)
## 
## Node number 253: 33 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6060606  P(node) =0.00165
##     class counts:     5    13     3    11     1
##    probabilities: 0.152 0.394 0.091 0.333 0.030 
##   left son=506 (20 obs) right son=507 (13 obs)
##   Primary splits:
##       age               < 79.5   to the left,  improve=3.605361, (0 missing)
##       arthritis         < 0.5    to the right, improve=2.541515, (0 missing)
##       cancer            < 0.5    to the right, improve=1.984848, (0 missing)
##       copd              < 0.5    to the right, improve=1.773737, (0 missing)
##       reimbursement2008 < 22825  to the left,  improve=1.341515, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 17295  to the right, agree=0.727, adj=0.308, (0 split)
##       bucket2008        < 3.5    to the right, agree=0.667, adj=0.154, (0 split)
##       heart.failure     < 0.5    to the right, agree=0.636, adj=0.077, (0 split)
## 
## Node number 254: 396 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6590909  P(node) =0.0198
##     class counts:    66   135    99    79    17
##    probabilities: 0.167 0.341 0.250 0.199 0.043 
##   left son=508 (233 obs) right son=509 (163 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=2.997912, (0 missing)
##       copd              < 0.5    to the left,  improve=1.877365, (0 missing)
##       age               < 49.5   to the right, improve=1.867161, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.727362, (0 missing)
##       reimbursement2008 < 23350  to the right, improve=1.426471, (0 missing)
##   Surrogate splits:
##       age               < 79.5   to the left,  agree=0.593, adj=0.012, (0 split)
##       reimbursement2008 < 15370  to the right, agree=0.593, adj=0.012, (0 split)
## 
## Node number 255: 487 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6201232  P(node) =0.02435
##     class counts:    37   185   104   136    25
##    probabilities: 0.076 0.380 0.214 0.279 0.051 
##   left son=510 (65 obs) right son=511 (422 obs)
##   Primary splits:
##       age               < 88.5   to the right, improve=4.7932710, (0 missing)
##       reimbursement2008 < 32590  to the left,  improve=2.4336710, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.5095490, (0 missing)
##       stroke            < 0.5    to the right, improve=1.4520590, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9634536, (0 missing)
## 
## Node number 320: 756 observations
##   predicted class=B1  expected loss=0.1216931  P(node) =0.0378
##     class counts:   664    57    27     7     1
##    probabilities: 0.878 0.075 0.036 0.009 0.001 
## 
## Node number 321: 830 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1626506  P(node) =0.0415
##     class counts:   695    80    41    12     2
##    probabilities: 0.837 0.096 0.049 0.014 0.002 
##   left son=642 (801 obs) right son=643 (29 obs)
##   Primary splits:
##       reimbursement2008 < 665    to the left,  improve=1.0300310, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4238073, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.4152878, (0 missing)
##       age               < 83.5   to the right, improve=0.3253936, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3055330, (0 missing)
## 
## Node number 322: 171 observations
##   predicted class=B1  expected loss=0.1812865  P(node) =0.00855
##     class counts:   140    21     7     3     0
##    probabilities: 0.819 0.123 0.041 0.018 0.000 
## 
## Node number 323: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     3     4     0     0     0
##    probabilities: 0.429 0.571 0.000 0.000 0.000 
## 
## Node number 352: 338 observations
##   predicted class=B1  expected loss=0.1745562  P(node) =0.0169
##     class counts:   279    29    20     8     2
##    probabilities: 0.825 0.086 0.059 0.024 0.006 
## 
## Node number 353: 206 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.223301  P(node) =0.0103
##     class counts:   160    31     6     9     0
##    probabilities: 0.777 0.150 0.029 0.044 0.000 
##   left son=706 (149 obs) right son=707 (57 obs)
##   Primary splits:
##       reimbursement2008 < 955    to the right, improve=2.3303040, (0 missing)
##       age               < 83.5   to the left,  improve=1.0927070, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.2820581, (0 missing)
##       depression        < 0.5    to the left,  improve=0.2779032, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2242064, (0 missing)
## 
## Node number 354: 182 observations
##   predicted class=B1  expected loss=0.2087912  P(node) =0.0091
##     class counts:   144    24     9     5     0
##    probabilities: 0.791 0.132 0.049 0.027 0.000 
## 
## Node number 355: 85 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3058824  P(node) =0.00425
##     class counts:    59    21     3     2     0
##    probabilities: 0.694 0.247 0.035 0.024 0.000 
##   left son=710 (76 obs) right son=711 (9 obs)
##   Primary splits:
##       reimbursement2008 < 785    to the left,  improve=1.6035430, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.6444788, (0 missing)
##       age               < 67.5   to the left,  improve=0.4285599, (0 missing)
##       kidney            < 0.5    to the right, improve=0.2709929, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2638534, (0 missing)
## 
## Node number 360: 449 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.2383073  P(node) =0.02245
##     class counts:   342    57    36    14     0
##    probabilities: 0.762 0.127 0.080 0.031 0.000 
##   left son=720 (283 obs) right son=721 (166 obs)
##   Primary splits:
##       reimbursement2008 < 1335   to the left,  improve=0.9925853, (0 missing)
##       age               < 86.5   to the right, improve=0.7150894, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.4184894, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.3114171, (0 missing)
##       copd              < 0.5    to the left,  improve=0.2866033, (0 missing)
##   Surrogate splits:
##       arthritis < 0.5    to the left,  agree=0.639, adj=0.024, (0 split)
##       cancer    < 0.5    to the left,  agree=0.635, adj=0.012, (0 split)
## 
## Node number 361: 137 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.3138686  P(node) =0.00685
##     class counts:    94    31     7     5     0
##    probabilities: 0.686 0.226 0.051 0.036 0.000 
##   left son=722 (50 obs) right son=723 (87 obs)
##   Primary splits:
##       reimbursement2008 < 1345   to the right, improve=0.88131890, (0 missing)
##       age               < 66.5   to the right, improve=0.69730870, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.63774780, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.09490691, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.05691905, (0 missing)
## 
## Node number 362: 143 observations,    complexity param=0.0001303838
##   predicted class=B1  expected loss=0.2937063  P(node) =0.00715
##     class counts:   101    28     8     4     2
##    probabilities: 0.706 0.196 0.056 0.028 0.014 
##   left son=724 (44 obs) right son=725 (99 obs)
##   Primary splits:
##       age               < 75.5   to the right, improve=1.3014760, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.1065060, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6625760, (0 missing)
##       reimbursement2008 < 1105   to the right, improve=0.6192812, (0 missing)
##       copd              < 0.5    to the right, improve=0.5462853, (0 missing)
## 
## Node number 363: 29 observations,    complexity param=0.0001303838
##   predicted class=B1  expected loss=0.5172414  P(node) =0.00145
##     class counts:    14    10     3     2     0
##    probabilities: 0.483 0.345 0.103 0.069 0.000 
##   left son=726 (17 obs) right son=727 (12 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=1.687965, (0 missing)
##       depression        < 0.5    to the right, improve=1.400383, (0 missing)
##       reimbursement2008 < 1230   to the right, improve=1.163009, (0 missing)
##       age               < 89.5   to the right, improve=1.116256, (0 missing)
##   Surrogate splits:
##       depression        < 0.5    to the left,  agree=0.690, adj=0.250, (0 split)
##       age               < 88     to the right, agree=0.655, adj=0.167, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.655, adj=0.167, (0 split)
##       arthritis         < 0.5    to the left,  agree=0.621, adj=0.083, (0 split)
##       reimbursement2008 < 1315   to the left,  agree=0.621, adj=0.083, (0 split)
## 
## Node number 368: 628 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.2563694  P(node) =0.0314
##     class counts:   467   104    43    12     2
##    probabilities: 0.744 0.166 0.068 0.019 0.003 
##   left son=736 (455 obs) right son=737 (173 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=1.5481310, (0 missing)
##       age               < 50     to the left,  improve=1.0731200, (0 missing)
##       reimbursement2008 < 1415   to the right, improve=0.7768717, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.6957436, (0 missing)
##       copd              < 0.5    to the right, improve=0.4845812, (0 missing)
##   Surrogate splits:
##       stroke < 0.5    to the left,  agree=0.726, adj=0.006, (0 split)
## 
## Node number 369: 63 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3650794  P(node) =0.00315
##     class counts:    40    15     7     1     0
##    probabilities: 0.635 0.238 0.111 0.016 0.000 
##   left son=738 (52 obs) right son=739 (11 obs)
##   Primary splits:
##       reimbursement2008 < 1485   to the right, improve=1.6751580, (0 missing)
##       age               < 77     to the left,  improve=1.2620310, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.8989344, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.8365607, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.4831933, (0 missing)
## 
## Node number 374: 35 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4857143  P(node) =0.00175
##     class counts:    18     9     5     3     0
##    probabilities: 0.514 0.257 0.143 0.086 0.000 
##   left son=748 (28 obs) right son=749 (7 obs)
##   Primary splits:
##       reimbursement2008 < 895    to the right, improve=1.2428570, (0 missing)
##       age               < 78.5   to the left,  improve=0.5571429, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1771429, (0 missing)
##       depression        < 0.5    to the right, improve=0.1771429, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.1695612, (0 missing)
##   Surrogate splits:
##       arthritis < 0.5    to the left,  agree=0.829, adj=0.143, (0 split)
## 
## Node number 375: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     1     5     2     0     0
##    probabilities: 0.125 0.625 0.250 0.000 0.000 
## 
## Node number 378: 310 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3193548  P(node) =0.0155
##     class counts:   211    65    24     9     1
##    probabilities: 0.681 0.210 0.077 0.029 0.003 
##   left son=756 (213 obs) right son=757 (97 obs)
##   Primary splits:
##       reimbursement2008 < 835    to the right, improve=1.2234200, (0 missing)
##       kidney            < 0.5    to the right, improve=0.9543067, (0 missing)
##       age               < 94.5   to the left,  improve=0.6199997, (0 missing)
##       copd              < 0.5    to the right, improve=0.5598660, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.3296654, (0 missing)
## 
## Node number 379: 12 observations
##   predicted class=B1  expected loss=0.6666667  P(node) =0.0006
##     class counts:     4     4     3     1     0
##    probabilities: 0.333 0.333 0.250 0.083 0.000 
## 
## Node number 380: 352 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4005682  P(node) =0.0176
##     class counts:   211    93    30    18     0
##    probabilities: 0.599 0.264 0.085 0.051 0.000 
##   left son=760 (242 obs) right son=761 (110 obs)
##   Primary splits:
##       depression    < 0.5    to the left,  improve=1.422004, (0 missing)
##       alzheimers    < 0.5    to the left,  improve=1.222427, (0 missing)
##       heart.failure < 0.5    to the left,  improve=1.193813, (0 missing)
##       kidney        < 0.5    to the left,  improve=1.141542, (0 missing)
##       age           < 41.5   to the left,  improve=1.015276, (0 missing)
##   Surrogate splits:
##       age < 31.5   to the right, agree=0.69, adj=0.009, (0 split)
## 
## Node number 381: 30 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4666667  P(node) =0.0015
##     class counts:    16     3     6     4     1
##    probabilities: 0.533 0.100 0.200 0.133 0.033 
##   left son=762 (22 obs) right son=763 (8 obs)
##   Primary splits:
##       age               < 70     to the right, improve=1.5590910, (0 missing)
##       reimbursement2008 < 1165   to the right, improve=0.3186603, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3000000, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.2421053, (0 missing)
##       depression        < 0.5    to the right, improve=0.1000000, (0 missing)
## 
## Node number 382: 7 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.00035
##     class counts:     5     1     1     0     0
##    probabilities: 0.714 0.143 0.143 0.000 0.000 
## 
## Node number 383: 18 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.0009
##     class counts:     3    10     3     2     0
##    probabilities: 0.167 0.556 0.167 0.111 0.000 
## 
## Node number 384: 395 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3012658  P(node) =0.01975
##     class counts:   276    70    39     9     1
##    probabilities: 0.699 0.177 0.099 0.023 0.003 
##   left son=768 (288 obs) right son=769 (107 obs)
##   Primary splits:
##       age               < 68.5   to the right, improve=1.6366860, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.9039390, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7765844, (0 missing)
##       reimbursement2008 < 2155   to the left,  improve=0.6564463, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5270843, (0 missing)
## 
## Node number 385: 122 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3934426  P(node) =0.0061
##     class counts:    74    30    11     7     0
##    probabilities: 0.607 0.246 0.090 0.057 0.000 
##   left son=770 (22 obs) right son=771 (100 obs)
##   Primary splits:
##       age               < 64     to the left,  improve=3.407899, (0 missing)
##       copd              < 0.5    to the left,  improve=2.182772, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.651095, (0 missing)
##       arthritis         < 0.5    to the right, improve=1.570224, (0 missing)
##       reimbursement2008 < 1715   to the left,  improve=1.522952, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2575   to the right, agree=0.828, adj=0.045, (0 split)
## 
## Node number 388: 45 observations
##   predicted class=B1  expected loss=0.2444444  P(node) =0.00225
##     class counts:    34     8     2     1     0
##    probabilities: 0.756 0.178 0.044 0.022 0.000 
## 
## Node number 389: 73 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.3972603  P(node) =0.00365
##     class counts:    44    23     4     1     1
##    probabilities: 0.603 0.315 0.055 0.014 0.014 
##   left son=778 (66 obs) right son=779 (7 obs)
##   Primary splits:
##       reimbursement2008 < 3390   to the left,  improve=1.0555650, (0 missing)
##       age               < 73.5   to the right, improve=0.9205119, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3975568, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.3383422, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.3014529, (0 missing)
## 
## Node number 390: 12 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0006
##     class counts:     8     3     0     1     0
##    probabilities: 0.667 0.250 0.000 0.083 0.000 
## 
## Node number 391: 26 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.3846154  P(node) =0.0013
##     class counts:     8    16     1     1     0
##    probabilities: 0.308 0.615 0.038 0.038 0.000 
##   left son=782 (7 obs) right son=783 (19 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=1.0289180, (0 missing)
##       age               < 71.5   to the left,  improve=0.9850816, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7134238, (0 missing)
##       reimbursement2008 < 2715   to the right, improve=0.6578089, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1266628, (0 missing)
##   Surrogate splits:
##       age < 83     to the right, agree=0.769, adj=0.143, (0 split)
## 
## Node number 394: 20 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.001
##     class counts:    15     3     0     2     0
##    probabilities: 0.750 0.150 0.000 0.100 0.000 
## 
## Node number 395: 58 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.5  P(node) =0.0029
##     class counts:    29    19     5     4     1
##    probabilities: 0.500 0.328 0.086 0.069 0.017 
##   left son=790 (50 obs) right son=791 (8 obs)
##   Primary splits:
##       reimbursement2008 < 2425   to the left,  improve=1.4217240, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.3465590, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.9017241, (0 missing)
##       age               < 71.5   to the right, improve=0.8647468, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.6097512, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.879, adj=0.125, (0 split)
## 
## Node number 396: 10 observations
##   predicted class=B1  expected loss=0.3  P(node) =0.0005
##     class counts:     7     0     3     0     0
##    probabilities: 0.700 0.000 0.300 0.000 0.000 
## 
## Node number 397: 130 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5461538  P(node) =0.0065
##     class counts:    59    43    24     3     1
##    probabilities: 0.454 0.331 0.185 0.023 0.008 
##   left son=794 (9 obs) right son=795 (121 obs)
##   Primary splits:
##       reimbursement2008 < 3265   to the right, improve=1.5391400, (0 missing)
##       age               < 79.5   to the left,  improve=1.1170220, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.0842510, (0 missing)
##       arthritis         < 0.5    to the right, improve=1.0803180, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.7807692, (0 missing)
##   Surrogate splits:
##       age < 48     to the left,  agree=0.938, adj=0.111, (0 split)
## 
## Node number 414: 12 observations
##   predicted class=B2  expected loss=0.4166667  P(node) =0.0006
##     class counts:     2     7     2     1     0
##    probabilities: 0.167 0.583 0.167 0.083 0.000 
## 
## Node number 415: 14 observations
##   predicted class=B3  expected loss=0.3571429  P(node) =0.0007
##     class counts:     1     3     9     1     0
##    probabilities: 0.071 0.214 0.643 0.071 0.000 
## 
## Node number 416: 307 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.3745928  P(node) =0.01535
##     class counts:   192    71    28    14     2
##    probabilities: 0.625 0.231 0.091 0.046 0.007 
##   left son=832 (163 obs) right son=833 (144 obs)
##   Primary splits:
##       diabetes          < 0.5    to the right, improve=1.8426850, (0 missing)
##       reimbursement2008 < 1595   to the right, improve=1.1555100, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.0463660, (0 missing)
##       cancer            < 0.5    to the right, improve=0.9571640, (0 missing)
##       age               < 88.5   to the left,  improve=0.9457736, (0 missing)
##   Surrogate splits:
##       age               < 75.5   to the right, agree=0.557, adj=0.056, (0 split)
##       reimbursement2008 < 1885   to the left,  agree=0.544, adj=0.028, (0 split)
## 
## Node number 417: 99 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.4747475  P(node) =0.00495
##     class counts:    52    34     7     5     1
##    probabilities: 0.525 0.343 0.071 0.051 0.010 
##   left son=834 (11 obs) right son=835 (88 obs)
##   Primary splits:
##       copd              < 0.5    to the right, improve=1.8888890, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.2998090, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.2183150, (0 missing)
##       reimbursement2008 < 2015   to the left,  improve=1.1747840, (0 missing)
##       age               < 88.5   to the left,  improve=0.8989783, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1615   to the left,  agree=0.909, adj=0.182, (0 split)
## 
## Node number 418: 261 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.4482759  P(node) =0.01305
##     class counts:   144    73    28    15     1
##    probabilities: 0.552 0.280 0.107 0.057 0.004 
##   left son=836 (228 obs) right son=837 (33 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=4.050652, (0 missing)
##       age               < 71.5   to the left,  improve=2.377089, (0 missing)
##       reimbursement2008 < 2485   to the left,  improve=1.974154, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.943678, (0 missing)
##       copd              < 0.5    to the left,  improve=1.910651, (0 missing)
## 
## Node number 419: 182 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.6098901  P(node) =0.0091
##     class counts:    71    68    29    11     3
##    probabilities: 0.390 0.374 0.159 0.060 0.016 
##   left son=838 (146 obs) right son=839 (36 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.1312160, (0 missing)
##       age               < 56.5   to the right, improve=2.0550500, (0 missing)
##       reimbursement2008 < 2235   to the left,  improve=1.8121880, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.1570780, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.5846992, (0 missing)
## 
## Node number 426: 15 observations
##   predicted class=B1  expected loss=0.5333333  P(node) =0.00075
##     class counts:     7     4     2     2     0
##    probabilities: 0.467 0.267 0.133 0.133 0.000 
## 
## Node number 427: 10 observations
##   predicted class=B2  expected loss=0.3  P(node) =0.0005
##     class counts:     2     7     0     1     0
##    probabilities: 0.200 0.700 0.000 0.100 0.000 
## 
## Node number 428: 162 observations,    complexity param=0.001064801
##   predicted class=B1  expected loss=0.5308642  P(node) =0.0081
##     class counts:    76    53    20    12     1
##    probabilities: 0.469 0.327 0.123 0.074 0.006 
##   left son=856 (76 obs) right son=857 (86 obs)
##   Primary splits:
##       reimbursement2008 < 1975   to the left,  improve=5.6805310, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.0157000, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8458215, (0 missing)
##       age               < 48.5   to the left,  improve=0.7356979, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.5696349, (0 missing)
##   Surrogate splits:
##       age          < 65.5   to the left,  agree=0.580, adj=0.105, (0 split)
##       osteoporosis < 0.5    to the right, agree=0.549, adj=0.039, (0 split)
##       diabetes     < 0.5    to the left,  agree=0.537, adj=0.013, (0 split)
##       stroke       < 0.5    to the right, agree=0.537, adj=0.013, (0 split)
## 
## Node number 429: 136 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.5294118  P(node) =0.0068
##     class counts:    46    64    23     3     0
##    probabilities: 0.338 0.471 0.169 0.022 0.000 
##   left son=858 (117 obs) right son=859 (19 obs)
##   Primary splits:
##       reimbursement2008 < 1705   to the right, improve=2.1418260, (0 missing)
##       age               < 77.5   to the right, improve=1.2623840, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7897266, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6677123, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.6652316, (0 missing)
## 
## Node number 432: 68 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.3529412  P(node) =0.0034
##     class counts:    44    18     3     3     0
##    probabilities: 0.647 0.265 0.044 0.044 0.000 
##   left son=864 (21 obs) right son=865 (47 obs)
##   Primary splits:
##       age               < 64.5   to the right, improve=2.2730500, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.3235290, (0 missing)
##       depression        < 0.5    to the left,  improve=1.1164500, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.9705882, (0 missing)
##       reimbursement2008 < 3195   to the left,  improve=0.9338624, (0 missing)
## 
## Node number 433: 213 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.4835681  P(node) =0.01065
##     class counts:   110    60    32     9     2
##    probabilities: 0.516 0.282 0.150 0.042 0.009 
##   left son=866 (92 obs) right son=867 (121 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=2.4788660, (0 missing)
##       reimbursement2008 < 3155   to the right, improve=1.9913470, (0 missing)
##       age               < 69.5   to the right, improve=1.9417030, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.1103130, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7492129, (0 missing)
##   Surrogate splits:
##       age               < 83.5   to the right, agree=0.577, adj=0.022, (0 split)
##       reimbursement2008 < 2535   to the left,  agree=0.573, adj=0.011, (0 split)
## 
## Node number 434: 10 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0005
##     class counts:     5     3     2     0     0
##    probabilities: 0.500 0.300 0.200 0.000 0.000 
## 
## Node number 435: 26 observations
##   predicted class=B2  expected loss=0.2692308  P(node) =0.0013
##     class counts:     3    19     4     0     0
##    probabilities: 0.115 0.731 0.154 0.000 0.000 
## 
## Node number 436: 146 observations,    complexity param=0.0006084576
##   predicted class=B1  expected loss=0.5547945  P(node) =0.0073
##     class counts:    65    52    16    13     0
##    probabilities: 0.445 0.356 0.110 0.089 0.000 
##   left son=872 (133 obs) right son=873 (13 obs)
##   Primary splits:
##       reimbursement2008 < 2585   to the right, improve=2.3843300, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.0271490, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.0118830, (0 missing)
##       depression        < 0.5    to the left,  improve=0.8908181, (0 missing)
##       age               < 74.5   to the left,  improve=0.8215784, (0 missing)
## 
## Node number 437: 67 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6567164  P(node) =0.00335
##     class counts:    18    23    17     9     0
##    probabilities: 0.269 0.343 0.254 0.134 0.000 
##   left son=874 (11 obs) right son=875 (56 obs)
##   Primary splits:
##       reimbursement2008 < 2605   to the left,  improve=0.8274375, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8104509, (0 missing)
##       age               < 58.5   to the left,  improve=0.7605544, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5110835, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=0.2925650, (0 missing)
##   Surrogate splits:
##       age < 47.5   to the left,  agree=0.881, adj=0.273, (0 split)
## 
## Node number 438: 57 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.4912281  P(node) =0.00285
##     class counts:    16    29     9     3     0
##    probabilities: 0.281 0.509 0.158 0.053 0.000 
##   left son=876 (41 obs) right son=877 (16 obs)
##   Primary splits:
##       reimbursement2008 < 2735   to the right, improve=2.1723900, (0 missing)
##       age               < 70.5   to the left,  improve=1.5686010, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.1967800, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6143996, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=0.4557416, (0 missing)
## 
## Node number 439: 27 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.5555556  P(node) =0.00135
##     class counts:     4    12    11     0     0
##    probabilities: 0.148 0.444 0.407 0.000 0.000 
##   left son=878 (9 obs) right son=879 (18 obs)
##   Primary splits:
##       age               < 84.5   to the right, improve=1.92592600, (0 missing)
##       reimbursement2008 < 3145   to the right, improve=0.29259260, (0 missing)
##       depression        < 0.5    to the left,  improve=0.29259260, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.20797720, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.07494553, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2695   to the left,  agree=0.741, adj=0.222, (0 split)
## 
## Node number 440: 150 observations,    complexity param=0.0002788764
##   predicted class=B2  expected loss=0.5533333  P(node) =0.0075
##     class counts:    50    67    27     5     1
##    probabilities: 0.333 0.447 0.180 0.033 0.007 
##   left son=880 (142 obs) right son=881 (8 obs)
##   Primary splits:
##       age               < 89.5   to the left,  improve=1.4895310, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.4218900, (0 missing)
##       reimbursement2008 < 2825   to the right, improve=1.3233330, (0 missing)
##       copd              < 0.5    to the left,  improve=1.2090920, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.9791534, (0 missing)
## 
## Node number 441: 7 observations
##   predicted class=B2  expected loss=0.1428571  P(node) =0.00035
##     class counts:     0     6     1     0     0
##    probabilities: 0.000 0.857 0.143 0.000 0.000 
## 
## Node number 444: 70 observations,    complexity param=0.000190143
##   predicted class=B2  expected loss=0.5  P(node) =0.0035
##     class counts:    22    35     8     4     1
##    probabilities: 0.314 0.500 0.114 0.057 0.014 
##   left son=888 (40 obs) right son=889 (30 obs)
##   Primary splits:
##       reimbursement2008 < 3265   to the left,  improve=2.1952380, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8206310, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.8196825, (0 missing)
##       copd              < 0.5    to the left,  improve=0.7659533, (0 missing)
##       age               < 82.5   to the right, improve=0.6993816, (0 missing)
##   Surrogate splits:
##       age           < 54.5   to the right, agree=0.614, adj=0.100, (0 split)
##       cancer        < 0.5    to the left,  agree=0.614, adj=0.100, (0 split)
##       heart.failure < 0.5    to the right, agree=0.614, adj=0.100, (0 split)
##       depression    < 0.5    to the right, agree=0.600, adj=0.067, (0 split)
## 
## Node number 445: 11 observations
##   predicted class=B2  expected loss=0.2727273  P(node) =0.00055
##     class counts:     1     8     0     2     0
##    probabilities: 0.091 0.727 0.000 0.182 0.000 
## 
## Node number 448: 120 observations,    complexity param=0.0001014096
##   predicted class=B1  expected loss=0.275  P(node) =0.006
##     class counts:    87    21     8     4     0
##    probabilities: 0.725 0.175 0.067 0.033 0.000 
##   left son=896 (26 obs) right son=897 (94 obs)
##   Primary splits:
##       reimbursement2008 < 8195   to the right, improve=1.9843150, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.6375210, (0 missing)
##       age               < 49.5   to the right, improve=1.1599100, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.1550330, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5544872, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.975, adj=0.885, (0 split)
## 
## Node number 449: 210 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.4380952  P(node) =0.0105
##     class counts:   118    56    28     6     2
##    probabilities: 0.562 0.267 0.133 0.029 0.010 
##   left son=898 (89 obs) right son=899 (121 obs)
##   Primary splits:
##       reimbursement2008 < 7060   to the right, improve=1.5649970, (0 missing)
##       age               < 59.5   to the right, improve=0.9328321, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.8837035, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.5471253, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4479437, (0 missing)
##   Surrogate splits:
##       bucket2008    < 2.5    to the right, agree=0.952, adj=0.888, (0 split)
##       kidney        < 0.5    to the right, agree=0.662, adj=0.202, (0 split)
##       age           < 83.5   to the right, agree=0.619, adj=0.101, (0 split)
##       heart.failure < 0.5    to the right, agree=0.619, adj=0.101, (0 split)
##       copd          < 0.5    to the right, agree=0.614, adj=0.090, (0 split)
## 
## Node number 450: 15 observations
##   predicted class=B1  expected loss=0.2  P(node) =0.00075
##     class counts:    12     1     1     1     0
##    probabilities: 0.800 0.067 0.067 0.067 0.000 
## 
## Node number 451: 74 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.5540541  P(node) =0.0037
##     class counts:    33    33     5     2     1
##    probabilities: 0.446 0.446 0.068 0.027 0.014 
##   left son=902 (60 obs) right son=903 (14 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.3193050, (0 missing)
##       age               < 66.5   to the left,  improve=1.1497330, (0 missing)
##       reimbursement2008 < 6655   to the left,  improve=0.9978265, (0 missing)
##       ihd               < 0.5    to the right, improve=0.5988288, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4239269, (0 missing)
##   Surrogate splits:
##       age               < 90.5   to the left,  agree=0.851, adj=0.214, (0 split)
##       reimbursement2008 < 11700  to the left,  agree=0.838, adj=0.143, (0 split)
## 
## Node number 452: 27 observations
##   predicted class=B1  expected loss=0.2962963  P(node) =0.00135
##     class counts:    19     4     1     3     0
##    probabilities: 0.704 0.148 0.037 0.111 0.000 
## 
## Node number 453: 31 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.6129032  P(node) =0.00155
##     class counts:    12    11     7     1     0
##    probabilities: 0.387 0.355 0.226 0.032 0.000 
##   left son=906 (16 obs) right son=907 (15 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the right, improve=0.9637097, (0 missing)
##       copd              < 0.5    to the right, improve=0.9101382, (0 missing)
##       reimbursement2008 < 4635   to the right, improve=0.7294660, (0 missing)
##       ihd               < 0.5    to the right, improve=0.6841642, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5193819, (0 missing)
##   Surrogate splits:
##       kidney            < 0.5    to the right, agree=0.710, adj=0.400, (0 split)
##       reimbursement2008 < 5195   to the right, agree=0.677, adj=0.333, (0 split)
##       age               < 68     to the right, agree=0.613, adj=0.200, (0 split)
##       ihd               < 0.5    to the right, agree=0.613, adj=0.200, (0 split)
##       copd              < 0.5    to the right, agree=0.581, adj=0.133, (0 split)
## 
## Node number 454: 14 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.0007
##     class counts:     8     3     2     1     0
##    probabilities: 0.571 0.214 0.143 0.071 0.000 
## 
## Node number 455: 72 observations,    complexity param=0.0003549336
##   predicted class=B2  expected loss=0.5972222  P(node) =0.0036
##     class counts:    22    29    19     2     0
##    probabilities: 0.306 0.403 0.264 0.028 0.000 
##   left son=910 (18 obs) right son=911 (54 obs)
##   Primary splits:
##       reimbursement2008 < 4780   to the left,  improve=1.4537040, (0 missing)
##       copd              < 0.5    to the right, improve=1.3585470, (0 missing)
##       age               < 80.5   to the right, improve=0.9255324, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.7387668, (0 missing)
##       kidney            < 0.5    to the right, improve=0.4950505, (0 missing)
## 
## Node number 456: 10 observations
##   predicted class=B2  expected loss=0.3  P(node) =0.0005
##     class counts:     2     7     1     0     0
##    probabilities: 0.200 0.700 0.100 0.000 0.000 
## 
## Node number 457: 32 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5  P(node) =0.0016
##     class counts:    16     8     3     5     0
##    probabilities: 0.500 0.250 0.094 0.156 0.000 
##   left son=914 (25 obs) right son=915 (7 obs)
##   Primary splits:
##       age               < 64.5   to the right, improve=1.3717860, (0 missing)
##       copd              < 0.5    to the left,  improve=1.3541670, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.8125000, (0 missing)
##       reimbursement2008 < 5140   to the left,  improve=0.5882937, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.2860714, (0 missing)
##   Surrogate splits:
##       arthritis < 0.5    to the left,  agree=0.812, adj=0.143, (0 split)
## 
## Node number 462: 12 observations
##   predicted class=B1  expected loss=0.5833333  P(node) =0.0006
##     class counts:     5     2     3     2     0
##    probabilities: 0.417 0.167 0.250 0.167 0.000 
## 
## Node number 463: 11 observations
##   predicted class=B3  expected loss=0.4545455  P(node) =0.00055
##     class counts:     1     4     6     0     0
##    probabilities: 0.091 0.364 0.545 0.000 0.000 
## 
## Node number 468: 72 observations,    complexity param=0.0006084576
##   predicted class=B2  expected loss=0.5277778  P(node) =0.0036
##     class counts:    28    34     7     3     0
##    probabilities: 0.389 0.472 0.097 0.042 0.000 
##   left son=936 (27 obs) right son=937 (45 obs)
##   Primary splits:
##       reimbursement2008 < 7260   to the right, improve=3.153704, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.757692, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.512060, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.494255, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.126923, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.903, adj=0.741, (0 split)
##       age        < 57.5   to the left,  agree=0.639, adj=0.037, (0 split)
##       kidney     < 0.5    to the right, agree=0.639, adj=0.037, (0 split)
## 
## Node number 469: 64 observations,    complexity param=0.0003549336
##   predicted class=B2  expected loss=0.5  P(node) =0.0032
##     class counts:    12    32    16     4     0
##    probabilities: 0.188 0.500 0.250 0.062 0.000 
##   left son=938 (12 obs) right son=939 (52 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=2.2692310, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.4314290, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.7790989, (0 missing)
##       reimbursement2008 < 23405  to the right, improve=0.7180451, (0 missing)
##       age               < 76.5   to the left,  improve=0.6937984, (0 missing)
## 
## Node number 470: 46 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.5217391  P(node) =0.0023
##     class counts:    22     9    10     5     0
##    probabilities: 0.478 0.196 0.217 0.109 0.000 
##   left son=940 (13 obs) right son=941 (33 obs)
##   Primary splits:
##       age               < 91.5   to the right, improve=2.1375290, (0 missing)
##       reimbursement2008 < 13835  to the left,  improve=1.6227110, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.1379310, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.9519520, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.6946237, (0 missing)
## 
## Node number 471: 11 observations
##   predicted class=B2  expected loss=0.4545455  P(node) =0.00055
##     class counts:     2     6     3     0     0
##    probabilities: 0.182 0.545 0.273 0.000 0.000 
## 
## Node number 478: 79 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.556962  P(node) =0.00395
##     class counts:    15    35    23     6     0
##    probabilities: 0.190 0.443 0.291 0.076 0.000 
##   left son=956 (41 obs) right son=957 (38 obs)
##   Primary splits:
##       age               < 75.5   to the left,  improve=0.9917453, (0 missing)
##       reimbursement2008 < 4785   to the left,  improve=0.9835014, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.7155960, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.6911068, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6784535, (0 missing)
##   Surrogate splits:
##       arthritis         < 0.5    to the left,  agree=0.658, adj=0.289, (0 split)
##       reimbursement2008 < 8635   to the left,  agree=0.633, adj=0.237, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.608, adj=0.184, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.582, adj=0.132, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.557, adj=0.079, (0 split)
## 
## Node number 479: 7 observations
##   predicted class=B1  expected loss=0.5714286  P(node) =0.00035
##     class counts:     3     1     1     2     0
##    probabilities: 0.429 0.143 0.143 0.286 0.000 
## 
## Node number 480: 199 observations,    complexity param=0.0008746577
##   predicted class=B1  expected loss=0.5477387  P(node) =0.00995
##     class counts:    90    72    32     5     0
##    probabilities: 0.452 0.362 0.161 0.025 0.000 
##   left son=960 (155 obs) right son=961 (44 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=4.0942290, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.4154020, (0 missing)
##       reimbursement2008 < 7230   to the right, improve=1.3220170, (0 missing)
##       age               < 62.5   to the right, improve=0.9109503, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.7457594, (0 missing)
##   Surrogate splits:
##       age < 31.5   to the right, agree=0.789, adj=0.045, (0 split)
## 
## Node number 481: 78 observations,    complexity param=0.000507048
##   predicted class=B1  expected loss=0.6923077  P(node) =0.0039
##     class counts:    24    19    20    14     1
##    probabilities: 0.308 0.244 0.256 0.179 0.013 
##   left son=962 (52 obs) right son=963 (26 obs)
##   Primary splits:
##       reimbursement2008 < 11475  to the right, improve=1.756410, (0 missing)
##       age               < 65.5   to the right, improve=1.591079, (0 missing)
##       depression        < 0.5    to the left,  improve=1.545455, (0 missing)
##       copd              < 0.5    to the left,  improve=1.292572, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.277778, (0 missing)
##   Surrogate splits:
##       ihd < 0.5    to the right, agree=0.705, adj=0.115, (0 split)
##       age < 49.5   to the right, agree=0.679, adj=0.038, (0 split)
## 
## Node number 482: 327 observations,    complexity param=0.0008746577
##   predicted class=B1  expected loss=0.6116208  P(node) =0.01635
##     class counts:   127   125    50    22     3
##    probabilities: 0.388 0.382 0.153 0.067 0.009 
##   left son=964 (170 obs) right son=965 (157 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=2.493752, (0 missing)
##       reimbursement2008 < 5355   to the left,  improve=2.213439, (0 missing)
##       age               < 97.5   to the left,  improve=2.016707, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.460516, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.183698, (0 missing)
##   Surrogate splits:
##       alzheimers        < 0.5    to the left,  agree=0.584, adj=0.134, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.572, adj=0.108, (0 split)
##       reimbursement2008 < 9565   to the left,  agree=0.566, adj=0.096, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.557, adj=0.076, (0 split)
##       age               < 80.5   to the left,  agree=0.554, adj=0.070, (0 split)
## 
## Node number 483: 187 observations,    complexity param=0.000380286
##   predicted class=B2  expected loss=0.4545455  P(node) =0.00935
##     class counts:    51   102    27     7     0
##    probabilities: 0.273 0.545 0.144 0.037 0.000 
##   left son=966 (74 obs) right son=967 (113 obs)
##   Primary splits:
##       age               < 77.5   to the left,  improve=1.8473350, (0 missing)
##       reimbursement2008 < 4720   to the left,  improve=1.8297120, (0 missing)
##       stroke            < 0.5    to the right, improve=0.8760224, (0 missing)
##       depression        < 0.5    to the right, improve=0.8148550, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.6872708, (0 missing)
## 
## Node number 486: 120 observations,    complexity param=0.0005324004
##   predicted class=B2  expected loss=0.6166667  P(node) =0.006
##     class counts:    25    46    38    11     0
##    probabilities: 0.208 0.383 0.317 0.092 0.000 
##   left son=972 (8 obs) right son=973 (112 obs)
##   Primary splits:
##       age               < 59.5   to the left,  improve=3.0630950, (0 missing)
##       reimbursement2008 < 6810   to the left,  improve=2.3493340, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.5126620, (0 missing)
##       depression        < 0.5    to the left,  improve=1.2818450, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.9859477, (0 missing)
## 
## Node number 487: 14 observations
##   predicted class=B3  expected loss=0.3571429  P(node) =0.0007
##     class counts:     3     2     9     0     0
##    probabilities: 0.214 0.143 0.643 0.000 0.000 
## 
## Node number 492: 183 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.557377  P(node) =0.00915
##     class counts:    52    81    23    23     4
##    probabilities: 0.284 0.443 0.126 0.126 0.022 
##   left son=984 (56 obs) right son=985 (127 obs)
##   Primary splits:
##       reimbursement2008 < 11200  to the right, improve=1.3922150, (0 missing)
##       age               < 67.5   to the right, improve=1.3360660, (0 missing)
##       copd              < 0.5    to the left,  improve=1.2442960, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.9452905, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9450073, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.907, adj=0.696, (0 split)
## 
## Node number 493: 99 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4747475  P(node) =0.00495
##     class counts:    16    52    21    10     0
##    probabilities: 0.162 0.525 0.212 0.101 0.000 
##   left son=986 (37 obs) right son=987 (62 obs)
##   Primary splits:
##       age               < 79.5   to the right, improve=2.3556310, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.3800430, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.2000000, (0 missing)
##       reimbursement2008 < 25605  to the right, improve=1.1394690, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9554113, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 13065  to the right, agree=0.657, adj=0.081, (0 split)
## 
## Node number 494: 241 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5435685  P(node) =0.01205
##     class counts:    46   110    62    21     2
##    probabilities: 0.191 0.456 0.257 0.087 0.008 
##   left son=988 (16 obs) right son=989 (225 obs)
##   Primary splits:
##       age               < 54.5   to the left,  improve=1.3463230, (0 missing)
##       reimbursement2008 < 4070   to the right, improve=1.3125650, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.3020150, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.0773410, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6861288, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 52960  to the right, agree=0.938, adj=0.062, (0 split)
##       bucket2008        < 4.5    to the right, agree=0.938, adj=0.062, (0 split)
## 
## Node number 495: 12 observations
##   predicted class=B3  expected loss=0.4166667  P(node) =0.0006
##     class counts:     0     5     7     0     0
##    probabilities: 0.000 0.417 0.583 0.000 0.000 
## 
## Node number 496: 346 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6531792  P(node) =0.0173
##     class counts:    88   120    71    57    10
##    probabilities: 0.254 0.347 0.205 0.165 0.029 
##   left son=992 (67 obs) right son=993 (279 obs)
##   Primary splits:
##       age               < 85.5   to the right, improve=2.853034, (0 missing)
##       reimbursement2008 < 6780   to the left,  improve=2.493960, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.888712, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.770580, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.127732, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 15040  to the right, agree=0.812, adj=0.03, (0 split)
## 
## Node number 497: 266 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.5902256  P(node) =0.0133
##     class counts:    50   109    68    33     6
##    probabilities: 0.188 0.410 0.256 0.124 0.023 
##   left son=994 (19 obs) right son=995 (247 obs)
##   Primary splits:
##       age               < 92.5   to the right, improve=3.1654140, (0 missing)
##       reimbursement2008 < 6185   to the left,  improve=2.8527200, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.0112500, (0 missing)
##       ihd               < 0.5    to the right, improve=0.9988659, (0 missing)
##       depression        < 0.5    to the right, improve=0.8363985, (0 missing)
## 
## Node number 498: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     0     4     3     0     0
##    probabilities: 0.000 0.571 0.429 0.000 0.000 
## 
## Node number 499: 19 observations
##   predicted class=B3  expected loss=0.3684211  P(node) =0.00095
##     class counts:     1     3    12     3     0
##    probabilities: 0.053 0.158 0.632 0.158 0.000 
## 
## Node number 500: 11 observations
##   predicted class=B2  expected loss=0.09090909  P(node) =0.00055
##     class counts:     0    10     0     1     0
##    probabilities: 0.000 0.909 0.000 0.091 0.000 
## 
## Node number 501: 132 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.4318182  P(node) =0.0066
##     class counts:    20    75    22    14     1
##    probabilities: 0.152 0.568 0.167 0.106 0.008 
##   left son=1002 (107 obs) right son=1003 (25 obs)
##   Primary splits:
##       reimbursement2008 < 4815   to the left,  improve=1.3622030, (0 missing)
##       age               < 80.5   to the right, improve=1.1112760, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7506887, (0 missing)
##       copd              < 0.5    to the right, improve=0.7453568, (0 missing)
##       cancer            < 0.5    to the right, improve=0.5247008, (0 missing)
## 
## Node number 502: 24 observations,    complexity param=0.0002028192
##   predicted class=B3  expected loss=0.6666667  P(node) =0.0012
##     class counts:     7     7     8     2     0
##    probabilities: 0.292 0.292 0.333 0.083 0.000 
##   left son=1004 (16 obs) right son=1005 (8 obs)
##   Primary splits:
##       age               < 70     to the right, improve=1.458333, (0 missing)
##       reimbursement2008 < 7185   to the right, improve=1.305556, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.261111, (0 missing)
##       depression        < 0.5    to the right, improve=1.083333, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.083333, (0 missing)
## 
## Node number 503: 285 observations,    complexity param=0.0002028192
##   predicted class=B2  expected loss=0.5263158  P(node) =0.01425
##     class counts:    29   135    77    38     6
##    probabilities: 0.102 0.474 0.270 0.133 0.021 
##   left son=1006 (253 obs) right son=1007 (32 obs)
##   Primary splits:
##       reimbursement2008 < 5725   to the right, improve=1.2734940, (0 missing)
##       age               < 95.5   to the right, improve=1.2461000, (0 missing)
##       copd              < 0.5    to the left,  improve=1.1568740, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.6666667, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.6302632, (0 missing)
## 
## Node number 504: 11 observations
##   predicted class=B1  expected loss=0.1818182  P(node) =0.00055
##     class counts:     9     0     1     1     0
##    probabilities: 0.818 0.000 0.091 0.091 0.000 
## 
## Node number 505: 9 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.00045
##     class counts:     2     5     0     2     0
##    probabilities: 0.222 0.556 0.000 0.222 0.000 
## 
## Node number 506: 20 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.4  P(node) =0.001
##     class counts:     1    12     2     4     1
##    probabilities: 0.050 0.600 0.100 0.200 0.050 
##   left son=1012 (13 obs) right son=1013 (7 obs)
##   Primary splits:
##       reimbursement2008 < 22825  to the left,  improve=4.1615380, (0 missing)
##       copd              < 0.5    to the right, improve=1.2757580, (0 missing)
##       age               < 68.5   to the right, improve=0.2833333, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.1000000, (0 missing)
##   Surrogate splits:
##       age          < 72.5   to the left,  agree=0.75, adj=0.286, (0 split)
##       osteoporosis < 0.5    to the left,  agree=0.75, adj=0.286, (0 split)
## 
## Node number 507: 13 observations
##   predicted class=B4  expected loss=0.4615385  P(node) =0.00065
##     class counts:     4     1     1     7     0
##    probabilities: 0.308 0.077 0.077 0.538 0.000 
## 
## Node number 508: 233 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6866953  P(node) =0.01165
##     class counts:    48    73    49    55     8
##    probabilities: 0.206 0.313 0.210 0.236 0.034 
##   left son=1016 (95 obs) right son=1017 (138 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.100995, (0 missing)
##       reimbursement2008 < 25650  to the right, improve=1.969720, (0 missing)
##       age               < 89.5   to the right, improve=1.419602, (0 missing)
##       stroke            < 0.5    to the right, improve=1.223362, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.077810, (0 missing)
##   Surrogate splits:
##       heart.failure < 0.5    to the left,  agree=0.609, adj=0.042, (0 split)
##       age           < 53.5   to the left,  agree=0.601, adj=0.021, (0 split)
## 
## Node number 509: 163 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6196319  P(node) =0.00815
##     class counts:    18    62    50    24     9
##    probabilities: 0.110 0.380 0.307 0.147 0.055 
##   left son=1018 (140 obs) right son=1019 (23 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the right, improve=2.091784, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.893817, (0 missing)
##       age               < 65     to the right, improve=1.795615, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.116333, (0 missing)
##       reimbursement2008 < 16525  to the right, improve=1.100480, (0 missing)
## 
## Node number 510: 65 observations
##   predicted class=B2  expected loss=0.4307692  P(node) =0.00325
##     class counts:     7    37     7    10     4
##    probabilities: 0.108 0.569 0.108 0.154 0.062 
## 
## Node number 511: 422 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6492891  P(node) =0.0211
##     class counts:    30   148    97   126    21
##    probabilities: 0.071 0.351 0.230 0.299 0.050 
##   left son=1022 (91 obs) right son=1023 (331 obs)
##   Primary splits:
##       reimbursement2008 < 32040  to the left,  improve=2.8304840, (0 missing)
##       stroke            < 0.5    to the right, improve=2.0316160, (0 missing)
##       age               < 34.5   to the left,  improve=1.6984130, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9304072, (0 missing)
##       bucket2008        < 4.5    to the right, improve=0.8586131, (0 missing)
## 
## Node number 642: 801 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1585518  P(node) =0.04005
##     class counts:   674    73    40    12     2
##    probabilities: 0.841 0.091 0.050 0.015 0.002 
##   left son=1284 (94 obs) right son=1285 (707 obs)
##   Primary splits:
##       reimbursement2008 < 245    to the left,  improve=0.4516579, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.3483743, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.3415246, (0 missing)
##       age               < 83.5   to the right, improve=0.3232539, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.2952273, (0 missing)
## 
## Node number 643: 29 observations
##   predicted class=B1  expected loss=0.2758621  P(node) =0.00145
##     class counts:    21     7     1     0     0
##    probabilities: 0.724 0.241 0.034 0.000 0.000 
## 
## Node number 706: 149 observations
##   predicted class=B1  expected loss=0.1677852  P(node) =0.00745
##     class counts:   124    18     3     4     0
##    probabilities: 0.832 0.121 0.020 0.027 0.000 
## 
## Node number 707: 57 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3684211  P(node) =0.00285
##     class counts:    36    13     3     5     0
##    probabilities: 0.632 0.228 0.053 0.088 0.000 
##   left son=1414 (43 obs) right son=1415 (14 obs)
##   Primary splits:
##       age               < 83.5   to the left,  improve=2.8778340, (0 missing)
##       reimbursement2008 < 945    to the left,  improve=1.6818210, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7156433, (0 missing)
## 
## Node number 710: 76 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2763158  P(node) =0.0038
##     class counts:    55    16     3     2     0
##    probabilities: 0.724 0.211 0.039 0.026 0.000 
##   left son=1420 (9 obs) right son=1421 (67 obs)
##   Primary splits:
##       age               < 81     to the right, improve=0.8204155, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5009717, (0 missing)
##       kidney            < 0.5    to the right, improve=0.4025050, (0 missing)
##       reimbursement2008 < 775    to the left,  improve=0.2718808, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2404084, (0 missing)
## 
## Node number 711: 9 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.00045
##     class counts:     4     5     0     0     0
##    probabilities: 0.444 0.556 0.000 0.000 0.000 
## 
## Node number 720: 283 observations,    complexity param=5.07048e-05
##   predicted class=B1  expected loss=0.2120141  P(node) =0.01415
##     class counts:   223    29    22     9     0
##    probabilities: 0.788 0.102 0.078 0.032 0.000 
##   left son=1440 (27 obs) right son=1441 (256 obs)
##   Primary splits:
##       age               < 87.5   to the right, improve=0.7753638, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.5910595, (0 missing)
##       reimbursement2008 < 1315   to the right, improve=0.5333621, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4097368, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.3159337, (0 missing)
## 
## Node number 721: 166 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.2831325  P(node) =0.0083
##     class counts:   119    28    14     5     0
##    probabilities: 0.717 0.169 0.084 0.030 0.000 
##   left son=1442 (158 obs) right son=1443 (8 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=0.7746302, (0 missing)
##       age               < 73.5   to the right, improve=0.7080149, (0 missing)
##       reimbursement2008 < 1525   to the right, improve=0.3417250, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3081519, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.2090240, (0 missing)
## 
## Node number 722: 50 observations
##   predicted class=B1  expected loss=0.26  P(node) =0.0025
##     class counts:    37     7     4     2     0
##    probabilities: 0.740 0.140 0.080 0.040 0.000 
## 
## Node number 723: 87 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.3448276  P(node) =0.00435
##     class counts:    57    24     3     3     0
##    probabilities: 0.655 0.276 0.034 0.034 0.000 
##   left son=1446 (52 obs) right son=1447 (35 obs)
##   Primary splits:
##       reimbursement2008 < 1235   to the left,  improve=1.3847290, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.0449780, (0 missing)
##       age               < 56.5   to the left,  improve=0.4942529, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.3668719, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.2869269, (0 missing)
##   Surrogate splits:
##       age        < 66.5   to the left,  agree=0.621, adj=0.057, (0 split)
##       depression < 0.5    to the left,  agree=0.609, adj=0.029, (0 split)
## 
## Node number 724: 44 observations
##   predicted class=B1  expected loss=0.1818182  P(node) =0.0022
##     class counts:    36     5     1     1     1
##    probabilities: 0.818 0.114 0.023 0.023 0.023 
## 
## Node number 725: 99 observations,    complexity param=0.0001303838
##   predicted class=B1  expected loss=0.3434343  P(node) =0.00495
##     class counts:    65    23     7     3     1
##    probabilities: 0.657 0.232 0.071 0.030 0.010 
##   left son=1450 (88 obs) right son=1451 (11 obs)
##   Primary splits:
##       age               < 73.5   to the left,  improve=3.2020200, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.8723440, (0 missing)
##       depression        < 0.5    to the left,  improve=1.3986170, (0 missing)
##       reimbursement2008 < 1495   to the left,  improve=0.6074520, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.4981241, (0 missing)
## 
## Node number 726: 17 observations
##   predicted class=B1  expected loss=0.3529412  P(node) =0.00085
##     class counts:    11     4     1     1     0
##    probabilities: 0.647 0.235 0.059 0.059 0.000 
## 
## Node number 727: 12 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0006
##     class counts:     3     6     2     1     0
##    probabilities: 0.250 0.500 0.167 0.083 0.000 
## 
## Node number 736: 455 observations
##   predicted class=B1  expected loss=0.2307692  P(node) =0.02275
##     class counts:   350    70    26     7     2
##    probabilities: 0.769 0.154 0.057 0.015 0.004 
## 
## Node number 737: 173 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3236994  P(node) =0.00865
##     class counts:   117    34    17     5     0
##    probabilities: 0.676 0.197 0.098 0.029 0.000 
##   left son=1474 (145 obs) right son=1475 (28 obs)
##   Primary splits:
##       reimbursement2008 < 820    to the right, improve=2.1496140, (0 missing)
##       copd              < 0.5    to the right, improve=1.2566750, (0 missing)
##       age               < 51     to the left,  improve=0.8052618, (0 missing)
##       depression        < 0.5    to the right, improve=0.7128829, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.2397510, (0 missing)
## 
## Node number 738: 52 observations
##   predicted class=B1  expected loss=0.3076923  P(node) =0.0026
##     class counts:    36    10     5     1     0
##    probabilities: 0.692 0.192 0.096 0.019 0.000 
## 
## Node number 739: 11 observations
##   predicted class=B2  expected loss=0.5454545  P(node) =0.00055
##     class counts:     4     5     2     0     0
##    probabilities: 0.364 0.455 0.182 0.000 0.000 
## 
## Node number 748: 28 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.0014
##     class counts:    16     7     2     3     0
##    probabilities: 0.571 0.250 0.071 0.107 0.000 
## 
## Node number 749: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     2     2     3     0     0
##    probabilities: 0.286 0.286 0.429 0.000 0.000 
## 
## Node number 756: 213 observations,    complexity param=6.084576e-05
##   predicted class=B1  expected loss=0.286385  P(node) =0.01065
##     class counts:   152    40    17     3     1
##    probabilities: 0.714 0.188 0.080 0.014 0.005 
##   left son=1512 (74 obs) right son=1513 (139 obs)
##   Primary splits:
##       age               < 79.5   to the right, improve=0.9593750, (0 missing)
##       reimbursement2008 < 1135   to the right, improve=0.8732722, (0 missing)
##       kidney            < 0.5    to the right, improve=0.6032588, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.5388738, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5312397, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1145   to the right, agree=0.676, adj=0.068, (0 split)
## 
## Node number 757: 97 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3917526  P(node) =0.00485
##     class counts:    59    25     7     6     0
##    probabilities: 0.608 0.258 0.072 0.062 0.000 
##   left son=1514 (68 obs) right son=1515 (29 obs)
##   Primary splits:
##       age               < 80.5   to the left,  improve=1.6903660, (0 missing)
##       reimbursement2008 < 825    to the left,  improve=1.2122050, (0 missing)
##       kidney            < 0.5    to the right, improve=0.6415946, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.3898343, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3406181, (0 missing)
##   Surrogate splits:
##       arthritis         < 0.5    to the left,  agree=0.711, adj=0.034, (0 split)
##       reimbursement2008 < 695    to the right, agree=0.711, adj=0.034, (0 split)
## 
## Node number 760: 242 observations
##   predicted class=B1  expected loss=0.3719008  P(node) =0.0121
##     class counts:   152    65    13    12     0
##    probabilities: 0.628 0.269 0.054 0.050 0.000 
## 
## Node number 761: 110 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4636364  P(node) =0.0055
##     class counts:    59    28    17     6     0
##    probabilities: 0.536 0.255 0.155 0.055 0.000 
##   left son=1522 (54 obs) right son=1523 (56 obs)
##   Primary splits:
##       age               < 70.5   to the left,  improve=1.6735210, (0 missing)
##       reimbursement2008 < 1215   to the right, improve=1.1616160, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.1244670, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.9812987, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5845740, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1435   to the right, agree=0.573, adj=0.130, (0 split)
##       kidney            < 0.5    to the right, agree=0.536, adj=0.056, (0 split)
##       copd              < 0.5    to the left,  agree=0.527, adj=0.037, (0 split)
##       alzheimers        < 0.5    to the right, agree=0.518, adj=0.019, (0 split)
##       heart.failure     < 0.5    to the right, agree=0.518, adj=0.019, (0 split)
## 
## Node number 762: 22 observations
##   predicted class=B1  expected loss=0.3636364  P(node) =0.0011
##     class counts:    14     2     4     1     1
##    probabilities: 0.636 0.091 0.182 0.045 0.045 
## 
## Node number 763: 8 observations
##   predicted class=B4  expected loss=0.625  P(node) =0.0004
##     class counts:     2     1     2     3     0
##    probabilities: 0.250 0.125 0.250 0.375 0.000 
## 
## Node number 768: 288 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.2743056  P(node) =0.0144
##     class counts:   209    43    28     8     0
##    probabilities: 0.726 0.149 0.097 0.028 0.000 
##   left son=1536 (47 obs) right son=1537 (241 obs)
##   Primary splits:
##       arthritis         < 0.5    to the right, improve=0.8439747, (0 missing)
##       reimbursement2008 < 1655   to the right, improve=0.6696734, (0 missing)
##       age               < 74.5   to the right, improve=0.6381027, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5456723, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.3289436, (0 missing)
## 
## Node number 769: 107 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3738318  P(node) =0.00535
##     class counts:    67    27    11     1     1
##    probabilities: 0.626 0.252 0.103 0.009 0.009 
##   left son=1538 (92 obs) right son=1539 (15 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=1.4783150, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7755357, (0 missing)
##       reimbursement2008 < 2050   to the right, improve=0.7622484, (0 missing)
##       age               < 52.5   to the right, improve=0.7367951, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.6885313, (0 missing)
## 
## Node number 770: 22 observations
##   predicted class=B1  expected loss=0.09090909  P(node) =0.0011
##     class counts:    20     2     0     0     0
##    probabilities: 0.909 0.091 0.000 0.000 0.000 
## 
## Node number 771: 100 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.46  P(node) =0.005
##     class counts:    54    28    11     7     0
##    probabilities: 0.540 0.280 0.110 0.070 0.000 
##   left son=1542 (72 obs) right son=1543 (28 obs)
##   Primary splits:
##       age               < 79.5   to the left,  improve=1.5182540, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.4808320, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.2877110, (0 missing)
##       reimbursement2008 < 2415   to the left,  improve=1.1369950, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.6141026, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2565   to the left,  agree=0.74, adj=0.071, (0 split)
## 
## Node number 778: 66 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.4090909  P(node) =0.0033
##     class counts:    39    23     3     0     1
##    probabilities: 0.591 0.348 0.045 0.000 0.015 
##   left son=1556 (41 obs) right son=1557 (25 obs)
##   Primary splits:
##       age               < 80.5   to the left,  improve=0.7254398, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.4378788, (0 missing)
##       reimbursement2008 < 3315   to the left,  improve=0.4004696, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3326730, (0 missing)
##       depression        < 0.5    to the left,  improve=0.3017677, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.667, adj=0.12, (0 split)
## 
## Node number 779: 7 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.00035
##     class counts:     5     0     1     1     0
##    probabilities: 0.714 0.000 0.143 0.143 0.000 
## 
## Node number 782: 7 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.00035
##     class counts:     4     3     0     0     0
##    probabilities: 0.571 0.429 0.000 0.000 0.000 
## 
## Node number 783: 19 observations
##   predicted class=B2  expected loss=0.3157895  P(node) =0.00095
##     class counts:     4    13     1     1     0
##    probabilities: 0.211 0.684 0.053 0.053 0.000 
## 
## Node number 790: 50 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.46  P(node) =0.0025
##     class counts:    27    16     2     4     1
##    probabilities: 0.540 0.320 0.040 0.080 0.020 
##   left son=1580 (26 obs) right son=1581 (24 obs)
##   Primary splits:
##       age               < 71.5   to the right, improve=1.2069230, (0 missing)
##       reimbursement2008 < 1800   to the right, improve=1.0050000, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.8916550, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.8085714, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2265   to the left,  agree=0.62, adj=0.208, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.56, adj=0.083, (0 split)
## 
## Node number 791: 8 observations
##   predicted class=B2  expected loss=0.625  P(node) =0.0004
##     class counts:     2     3     3     0     0
##    probabilities: 0.250 0.375 0.375 0.000 0.000 
## 
## Node number 794: 9 observations
##   predicted class=B1  expected loss=0.2222222  P(node) =0.00045
##     class counts:     7     1     1     0     0
##    probabilities: 0.778 0.111 0.111 0.000 0.000 
## 
## Node number 795: 121 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5702479  P(node) =0.00605
##     class counts:    52    42    23     3     1
##    probabilities: 0.430 0.347 0.190 0.025 0.008 
##   left son=1590 (113 obs) right son=1591 (8 obs)
##   Primary splits:
##       reimbursement2008 < 3190   to the left,  improve=1.4937290, (0 missing)
##       age               < 83.5   to the left,  improve=1.2045730, (0 missing)
##       arthritis         < 0.5    to the right, improve=1.1497890, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.1433640, (0 missing)
##       cancer            < 0.5    to the right, improve=0.5801522, (0 missing)
## 
## Node number 832: 163 observations
##   predicted class=B1  expected loss=0.3374233  P(node) =0.00815
##     class counts:   108    28    18     8     1
##    probabilities: 0.663 0.172 0.110 0.049 0.006 
## 
## Node number 833: 144 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.4166667  P(node) =0.0072
##     class counts:    84    43    10     6     1
##    probabilities: 0.583 0.299 0.069 0.042 0.007 
##   left son=1666 (86 obs) right son=1667 (58 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=2.003041, (0 missing)
##       reimbursement2008 < 2295   to the left,  improve=1.394463, (0 missing)
##       age               < 96     to the right, improve=1.318865, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.140392, (0 missing)
##       copd              < 0.5    to the left,  improve=1.104582, (0 missing)
##   Surrogate splits:
##       kidney            < 0.5    to the left,  agree=0.632, adj=0.086, (0 split)
##       age               < 84.5   to the left,  agree=0.618, adj=0.052, (0 split)
##       reimbursement2008 < 2475   to the left,  agree=0.604, adj=0.017, (0 split)
## 
## Node number 834: 11 observations
##   predicted class=B1  expected loss=0.1818182  P(node) =0.00055
##     class counts:     9     1     1     0     0
##    probabilities: 0.818 0.091 0.091 0.000 0.000 
## 
## Node number 835: 88 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.5113636  P(node) =0.0044
##     class counts:    43    33     6     5     1
##    probabilities: 0.489 0.375 0.068 0.057 0.011 
##   left son=1670 (63 obs) right son=1671 (25 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=1.364329, (0 missing)
##       age               < 88.5   to the left,  improve=1.315651, (0 missing)
##       reimbursement2008 < 1675   to the right, improve=1.302389, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.227954, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.034774, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1665   to the right, agree=0.739, adj=0.08, (0 split)
## 
## Node number 836: 228 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.4078947  P(node) =0.0114
##     class counts:   135    61    20    11     1
##    probabilities: 0.592 0.268 0.088 0.048 0.004 
##   left son=1672 (218 obs) right son=1673 (10 obs)
##   Primary splits:
##       age               < 43.5   to the right, improve=2.3332050, (0 missing)
##       reimbursement2008 < 2485   to the left,  improve=2.1917580, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.7231690, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4130781, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3314113, (0 missing)
## 
## Node number 837: 33 observations,    complexity param=0.000380286
##   predicted class=B2  expected loss=0.6363636  P(node) =0.00165
##     class counts:     9    12     8     4     0
##    probabilities: 0.273 0.364 0.242 0.121 0.000 
##   left son=1674 (26 obs) right son=1675 (7 obs)
##   Primary splits:
##       age               < 72.5   to the left,  improve=2.8235100, (0 missing)
##       reimbursement2008 < 2185   to the right, improve=1.9883450, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.3051950, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.9114219, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5432900, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.848, adj=0.286, (0 split)
## 
## Node number 838: 146 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5821918  P(node) =0.0073
##     class counts:    56    61    19     8     2
##    probabilities: 0.384 0.418 0.130 0.055 0.014 
##   left son=1676 (115 obs) right son=1677 (31 obs)
##   Primary splits:
##       reimbursement2008 < 2235   to the left,  improve=1.5612480, (0 missing)
##       age               < 57     to the right, improve=1.4223930, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.7955683, (0 missing)
##       cancer            < 0.5    to the right, improve=0.5672709, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4457929, (0 missing)
## 
## Node number 839: 36 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.5833333  P(node) =0.0018
##     class counts:    15     7    10     3     1
##    probabilities: 0.417 0.194 0.278 0.083 0.028 
##   left son=1678 (11 obs) right son=1679 (25 obs)
##   Primary splits:
##       age               < 69.5   to the right, improve=1.3915150, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.1487180, (0 missing)
##       reimbursement2008 < 1805   to the left,  improve=1.0180620, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.8888889, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.2095875, (0 missing)
## 
## Node number 856: 76 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.3684211  P(node) =0.0038
##     class counts:    48    18     4     5     1
##    probabilities: 0.632 0.237 0.053 0.066 0.013 
##   left son=1712 (62 obs) right son=1713 (14 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=1.9467620, (0 missing)
##       reimbursement2008 < 1865   to the right, improve=1.2898500, (0 missing)
##       age               < 65.5   to the right, improve=1.1346230, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.9830044, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8057033, (0 missing)
## 
## Node number 857: 86 observations,    complexity param=0.0006084576
##   predicted class=B2  expected loss=0.5930233  P(node) =0.0043
##     class counts:    28    35    16     7     0
##    probabilities: 0.326 0.407 0.186 0.081 0.000 
##   left son=1714 (54 obs) right son=1715 (32 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=2.0120050, (0 missing)
##       reimbursement2008 < 2425   to the right, improve=1.7270100, (0 missing)
##       age               < 62.5   to the right, improve=1.4082940, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.0133720, (0 missing)
##       kidney            < 0.5    to the right, improve=0.7368141, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1995   to the right, agree=0.64, adj=0.031, (0 split)
## 
## Node number 858: 117 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.4871795  P(node) =0.00585
##     class counts:    39    60    17     1     0
##    probabilities: 0.333 0.513 0.145 0.009 0.000 
##   left son=1716 (8 obs) right son=1717 (109 obs)
##   Primary splits:
##       reimbursement2008 < 2445   to the right, improve=1.3278250, (0 missing)
##       age               < 77.5   to the right, improve=0.8223648, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.6487584, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5676773, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.3698183, (0 missing)
## 
## Node number 859: 19 observations
##   predicted class=B1  expected loss=0.6315789  P(node) =0.00095
##     class counts:     7     4     6     2     0
##    probabilities: 0.368 0.211 0.316 0.105 0.000 
## 
## Node number 864: 21 observations
##   predicted class=B1  expected loss=0.1428571  P(node) =0.00105
##     class counts:    18     2     0     1     0
##    probabilities: 0.857 0.095 0.000 0.048 0.000 
## 
## Node number 865: 47 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4468085  P(node) =0.00235
##     class counts:    26    16     3     2     0
##    probabilities: 0.553 0.340 0.064 0.043 0.000 
##   left son=1730 (37 obs) right son=1731 (10 obs)
##   Primary splits:
##       reimbursement2008 < 2765   to the right, improve=1.2287520, (0 missing)
##       depression        < 0.5    to the left,  improve=1.1399940, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.1047280, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7825059, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.7595591, (0 missing)
## 
## Node number 866: 92 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.3804348  P(node) =0.0046
##     class counts:    57    21    10     4     0
##    probabilities: 0.620 0.228 0.109 0.043 0.000 
##   left son=1732 (23 obs) right son=1733 (69 obs)
##   Primary splits:
##       reimbursement2008 < 3170   to the right, improve=1.9927540, (0 missing)
##       age               < 83.5   to the left,  improve=1.0853600, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.0471420, (0 missing)
##       copd              < 0.5    to the left,  improve=0.9387681, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.5135517, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the right, agree=0.848, adj=0.391, (0 split)
##       age        < 89.5   to the right, agree=0.761, adj=0.043, (0 split)
## 
## Node number 867: 121 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.5619835  P(node) =0.00605
##     class counts:    53    39    22     5     2
##    probabilities: 0.438 0.322 0.182 0.041 0.017 
##   left son=1734 (104 obs) right son=1735 (17 obs)
##   Primary splits:
##       age               < 69.5   to the right, improve=2.7636680, (0 missing)
##       reimbursement2008 < 2675   to the left,  improve=1.1093730, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.9745305, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.9029175, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5339984, (0 missing)
## 
## Node number 872: 133 observations,    complexity param=0.0006084576
##   predicted class=B1  expected loss=0.5263158  P(node) =0.00665
##     class counts:    63    48    11    11     0
##    probabilities: 0.474 0.361 0.083 0.083 0.000 
##   left son=1744 (8 obs) right son=1745 (125 obs)
##   Primary splits:
##       reimbursement2008 < 3365   to the right, improve=1.9610380, (0 missing)
##       age               < 69.5   to the left,  improve=1.5783450, (0 missing)
##       depression        < 0.5    to the left,  improve=1.1410180, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.9988038, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.7504819, (0 missing)
## 
## Node number 873: 13 observations
##   predicted class=B3  expected loss=0.6153846  P(node) =0.00065
##     class counts:     2     4     5     2     0
##    probabilities: 0.154 0.308 0.385 0.154 0.000 
## 
## Node number 874: 11 observations
##   predicted class=B1  expected loss=0.5454545  P(node) =0.00055
##     class counts:     5     2     3     1     0
##    probabilities: 0.455 0.182 0.273 0.091 0.000 
## 
## Node number 875: 56 observations,    complexity param=0.0003549336
##   predicted class=B2  expected loss=0.625  P(node) =0.0028
##     class counts:    13    21    14     8     0
##    probabilities: 0.232 0.375 0.250 0.143 0.000 
##   left son=1750 (10 obs) right son=1751 (46 obs)
##   Primary splits:
##       reimbursement2008 < 2755   to the left,  improve=1.7947200, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6517857, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5812448, (0 missing)
##       age               < 82.5   to the right, improve=0.5119048, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=0.1398924, (0 missing)
## 
## Node number 876: 41 observations
##   predicted class=B2  expected loss=0.3902439  P(node) =0.00205
##     class counts:     9    25     6     1     0
##    probabilities: 0.220 0.610 0.146 0.024 0.000 
## 
## Node number 877: 16 observations
##   predicted class=B1  expected loss=0.5625  P(node) =0.0008
##     class counts:     7     4     3     2     0
##    probabilities: 0.438 0.250 0.188 0.125 0.000 
## 
## Node number 878: 9 observations
##   predicted class=B1  expected loss=0.5555556  P(node) =0.00045
##     class counts:     4     2     3     0     0
##    probabilities: 0.444 0.222 0.333 0.000 0.000 
## 
## Node number 879: 18 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.0009
##     class counts:     0    10     8     0     0
##    probabilities: 0.000 0.556 0.444 0.000 0.000 
## 
## Node number 880: 142 observations,    complexity param=0.0002788764
##   predicted class=B2  expected loss=0.5704225  P(node) =0.0071
##     class counts:    49    61    27     4     1
##    probabilities: 0.345 0.430 0.190 0.028 0.007 
##   left son=1760 (104 obs) right son=1761 (38 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=1.5963530, (0 missing)
##       reimbursement2008 < 2805   to the right, improve=1.3502880, (0 missing)
##       copd              < 0.5    to the left,  improve=1.1429120, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.0117310, (0 missing)
##       age               < 66.5   to the left,  improve=0.9566806, (0 missing)
## 
## Node number 881: 8 observations
##   predicted class=B2  expected loss=0.25  P(node) =0.0004
##     class counts:     1     6     0     1     0
##    probabilities: 0.125 0.750 0.000 0.125 0.000 
## 
## Node number 888: 40 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.575  P(node) =0.002
##     class counts:    17    16     5     1     1
##    probabilities: 0.425 0.400 0.125 0.025 0.025 
##   left son=1776 (11 obs) right son=1777 (29 obs)
##   Primary splits:
##       age               < 82.5   to the right, improve=1.2360500, (0 missing)
##       copd              < 0.5    to the left,  improve=1.0506490, (0 missing)
##       reimbursement2008 < 3215   to the right, improve=0.7666667, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.7606061, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.5901099, (0 missing)
## 
## Node number 889: 30 observations
##   predicted class=B2  expected loss=0.3666667  P(node) =0.0015
##     class counts:     5    19     3     3     0
##    probabilities: 0.167 0.633 0.100 0.100 0.000 
## 
## Node number 896: 26 observations
##   predicted class=B1  expected loss=0.07692308  P(node) =0.0013
##     class counts:    24     1     1     0     0
##    probabilities: 0.923 0.038 0.038 0.000 0.000 
## 
## Node number 897: 94 observations,    complexity param=0.0001014096
##   predicted class=B1  expected loss=0.3297872  P(node) =0.0047
##     class counts:    63    20     7     4     0
##    probabilities: 0.670 0.213 0.074 0.043 0.000 
##   left son=1794 (64 obs) right son=1795 (30 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=1.4985370, (0 missing)
##       age               < 49.5   to the right, improve=1.2949040, (0 missing)
##       reimbursement2008 < 3800   to the left,  improve=1.1582080, (0 missing)
##       copd              < 0.5    to the left,  improve=0.9964539, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.4900436, (0 missing)
##   Surrogate splits:
##       age               < 91.5   to the left,  agree=0.723, adj=0.133, (0 split)
##       stroke            < 0.5    to the left,  agree=0.723, adj=0.133, (0 split)
##       copd              < 0.5    to the left,  agree=0.702, adj=0.067, (0 split)
##       reimbursement2008 < 7705   to the left,  agree=0.691, adj=0.033, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.691, adj=0.033, (0 split)
## 
## Node number 898: 89 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3595506  P(node) =0.00445
##     class counts:    57    21     7     3     1
##    probabilities: 0.640 0.236 0.079 0.034 0.011 
##   left son=1796 (22 obs) right son=1797 (67 obs)
##   Primary splits:
##       reimbursement2008 < 9310   to the left,  improve=2.1396340, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.6199640, (0 missing)
##       copd              < 0.5    to the left,  improve=0.9273400, (0 missing)
##       age               < 59.5   to the right, improve=0.8270218, (0 missing)
##       stroke            < 0.5    to the right, improve=0.8268807, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.865, adj=0.455, (0 split)
##       age        < 94.5   to the right, agree=0.775, adj=0.091, (0 split)
## 
## Node number 899: 121 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.4958678  P(node) =0.00605
##     class counts:    61    35    21     3     1
##    probabilities: 0.504 0.289 0.174 0.025 0.008 
##   left son=1798 (105 obs) right son=1799 (16 obs)
##   Primary splits:
##       reimbursement2008 < 6145   to the left,  improve=3.6574090, (0 missing)
##       age               < 88.5   to the right, improve=1.6732430, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.4740051, (0 missing)
##       kidney            < 0.5    to the right, improve=0.3966942, (0 missing)
##       copd              < 0.5    to the left,  improve=0.2864993, (0 missing)
## 
## Node number 902: 60 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.5  P(node) =0.003
##     class counts:    30    23     5     2     0
##    probabilities: 0.500 0.383 0.083 0.033 0.000 
##   left son=1804 (26 obs) right son=1805 (34 obs)
##   Primary splits:
##       age               < 74.5   to the left,  improve=1.7361990, (0 missing)
##       reimbursement2008 < 9210   to the right, improve=1.6200000, (0 missing)
##       ihd               < 0.5    to the right, improve=1.1258370, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.5012422, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.4916667, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 3905   to the left,  agree=0.667, adj=0.231, (0 split)
##       stroke            < 0.5    to the right, agree=0.600, adj=0.077, (0 split)
## 
## Node number 903: 14 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.0007
##     class counts:     3    10     0     0     1
##    probabilities: 0.214 0.714 0.000 0.000 0.071 
## 
## Node number 906: 16 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0008
##     class counts:     5     8     3     0     0
##    probabilities: 0.312 0.500 0.188 0.000 0.000 
## 
## Node number 907: 15 observations
##   predicted class=B1  expected loss=0.5333333  P(node) =0.00075
##     class counts:     7     3     4     1     0
##    probabilities: 0.467 0.200 0.267 0.067 0.000 
## 
## Node number 910: 18 observations
##   predicted class=B2  expected loss=0.3888889  P(node) =0.0009
##     class counts:     4    11     3     0     0
##    probabilities: 0.222 0.611 0.167 0.000 0.000 
## 
## Node number 911: 54 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.6666667  P(node) =0.0027
##     class counts:    18    18    16     2     0
##    probabilities: 0.333 0.333 0.296 0.037 0.000 
##   left son=1822 (22 obs) right son=1823 (32 obs)
##   Primary splits:
##       reimbursement2008 < 13120  to the right, improve=1.9920030, (0 missing)
##       copd              < 0.5    to the right, improve=1.6851850, (0 missing)
##       kidney            < 0.5    to the right, improve=0.7220273, (0 missing)
##       age               < 81.5   to the right, improve=0.6681397, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.4629630, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.796, adj=0.500, (0 split)
##       age        < 94.5   to the right, agree=0.667, adj=0.182, (0 split)
##       kidney     < 0.5    to the right, agree=0.611, adj=0.045, (0 split)
## 
## Node number 914: 25 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.48  P(node) =0.00125
##     class counts:    13     7     0     5     0
##    probabilities: 0.520 0.280 0.000 0.200 0.000 
##   left son=1828 (18 obs) right son=1829 (7 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=1.3911110, (0 missing)
##       age               < 71.5   to the right, improve=0.7994805, (0 missing)
##       reimbursement2008 < 5140   to the left,  improve=0.6774359, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.3059740, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 5705   to the left,  agree=0.76, adj=0.143, (0 split)
## 
## Node number 915: 7 observations
##   predicted class=B1  expected loss=0.5714286  P(node) =0.00035
##     class counts:     3     1     3     0     0
##    probabilities: 0.429 0.143 0.429 0.000 0.000 
## 
## Node number 936: 27 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4074074  P(node) =0.00135
##     class counts:    16     8     2     1     0
##    probabilities: 0.593 0.296 0.074 0.037 0.000 
##   left son=1872 (11 obs) right son=1873 (16 obs)
##   Primary splits:
##       reimbursement2008 < 14045  to the right, improve=1.6334180, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.3152360, (0 missing)
##       kidney            < 0.5    to the right, improve=0.9629630, (0 missing)
##       age               < 69.5   to the right, improve=0.8518519, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7261209, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.778, adj=0.455, (0 split)
##       age        < 77.5   to the right, agree=0.704, adj=0.273, (0 split)
## 
## Node number 937: 45 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.4222222  P(node) =0.00225
##     class counts:    12    26     5     2     0
##    probabilities: 0.267 0.578 0.111 0.044 0.000 
##   left son=1874 (7 obs) right son=1875 (38 obs)
##   Primary splits:
##       reimbursement2008 < 3740   to the left,  improve=1.5017540, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7257703, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.6939394, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5049550, (0 missing)
##       kidney            < 0.5    to the right, improve=0.4306306, (0 missing)
## 
## Node number 938: 12 observations
##   predicted class=B2  expected loss=0.1666667  P(node) =0.0006
##     class counts:     1    10     1     0     0
##    probabilities: 0.083 0.833 0.083 0.000 0.000 
## 
## Node number 939: 52 observations,    complexity param=0.0003549336
##   predicted class=B2  expected loss=0.5769231  P(node) =0.0026
##     class counts:    11    22    15     4     0
##    probabilities: 0.212 0.423 0.288 0.077 0.000 
##   left son=1878 (13 obs) right son=1879 (39 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=2.0897440, (0 missing)
##       age               < 79.5   to the right, improve=1.0514040, (0 missing)
##       reimbursement2008 < 5860   to the right, improve=1.0026590, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.9019404, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.6196581, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 3925   to the left,  agree=0.769, adj=0.077, (0 split)
## 
## Node number 940: 13 observations
##   predicted class=B1  expected loss=0.2307692  P(node) =0.00065
##     class counts:    10     2     1     0     0
##    probabilities: 0.769 0.154 0.077 0.000 0.000 
## 
## Node number 941: 33 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.6363636  P(node) =0.00165
##     class counts:    12     7     9     5     0
##    probabilities: 0.364 0.212 0.273 0.152 0.000 
##   left son=1882 (26 obs) right son=1883 (7 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=1.4778550, (0 missing)
##       reimbursement2008 < 10080  to the left,  improve=1.4293940, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.9393939, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7727273, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7575758, (0 missing)
## 
## Node number 956: 41 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.6097561  P(node) =0.00205
##     class counts:    11    16    10     4     0
##    probabilities: 0.268 0.390 0.244 0.098 0.000 
##   left son=1912 (30 obs) right son=1913 (11 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=1.8119730, (0 missing)
##       reimbursement2008 < 5410   to the left,  improve=1.1877310, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.8998522, (0 missing)
##       age               < 70.5   to the right, improve=0.8138451, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.7968658, (0 missing)
##   Surrogate splits:
##       age    < 37     to the right, agree=0.756, adj=0.091, (0 split)
##       stroke < 0.5    to the left,  agree=0.756, adj=0.091, (0 split)
## 
## Node number 957: 38 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.5  P(node) =0.0019
##     class counts:     4    19    13     2     0
##    probabilities: 0.105 0.500 0.342 0.053 0.000 
##   left son=1914 (31 obs) right son=1915 (7 obs)
##   Primary splits:
##       reimbursement2008 < 4300   to the right, improve=2.3189430, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.0000000, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.9492850, (0 missing)
##       age               < 81.5   to the left,  improve=0.7535885, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.6058612, (0 missing)
##   Surrogate splits:
##       age < 92.5   to the left,  agree=0.842, adj=0.143, (0 split)
## 
## Node number 960: 155 observations,    complexity param=0.0003422574
##   predicted class=B1  expected loss=0.5032258  P(node) =0.00775
##     class counts:    77    47    28     3     0
##    probabilities: 0.497 0.303 0.181 0.019 0.000 
##   left son=1920 (32 obs) right son=1921 (123 obs)
##   Primary splits:
##       reimbursement2008 < 6290   to the right, improve=1.7144870, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.3927660, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.5998232, (0 missing)
##       age               < 66.5   to the left,  improve=0.5282028, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.2484000, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.852, adj=0.281, (0 split)
## 
## Node number 961: 44 observations
##   predicted class=B2  expected loss=0.4318182  P(node) =0.0022
##     class counts:    13    25     4     2     0
##    probabilities: 0.295 0.568 0.091 0.045 0.000 
## 
## Node number 962: 52 observations,    complexity param=0.000507048
##   predicted class=B1  expected loss=0.6923077  P(node) =0.0026
##     class counts:    16    16     9    10     1
##    probabilities: 0.308 0.308 0.173 0.192 0.019 
##   left son=1924 (31 obs) right son=1925 (21 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=1.6461660, (0 missing)
##       age               < 52     to the right, improve=1.5856640, (0 missing)
##       reimbursement2008 < 13440  to the right, improve=1.1403330, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.9728254, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7932401, (0 missing)
##   Surrogate splits:
##       age               < 50.5   to the right, agree=0.654, adj=0.143, (0 split)
##       stroke            < 0.5    to the left,  agree=0.654, adj=0.143, (0 split)
##       depression        < 0.5    to the left,  agree=0.635, adj=0.095, (0 split)
##       reimbursement2008 < 16130  to the left,  agree=0.615, adj=0.048, (0 split)
## 
## Node number 963: 26 observations,    complexity param=0.0001521144
##   predicted class=B3  expected loss=0.5769231  P(node) =0.0013
##     class counts:     8     3    11     4     0
##    probabilities: 0.308 0.115 0.423 0.154 0.000 
##   left son=1926 (15 obs) right son=1927 (11 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=1.1109560, (0 missing)
##       reimbursement2008 < 10135  to the right, improve=0.9468864, (0 missing)
##       age               < 65     to the right, improve=0.5480769, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5064103, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.4720965, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 9215   to the right, agree=0.692, adj=0.273, (0 split)
##       age               < 68.5   to the left,  agree=0.654, adj=0.182, (0 split)
##       stroke            < 0.5    to the left,  agree=0.654, adj=0.182, (0 split)
##       ihd               < 0.5    to the right, agree=0.615, adj=0.091, (0 split)
## 
## Node number 964: 170 observations,    complexity param=0.0004563432
##   predicted class=B1  expected loss=0.5411765  P(node) =0.0085
##     class counts:    78    58    23    10     1
##    probabilities: 0.459 0.341 0.135 0.059 0.006 
##   left son=1928 (144 obs) right son=1929 (26 obs)
##   Primary splits:
##       age               < 88.5   to the left,  improve=2.0616640, (0 missing)
##       reimbursement2008 < 5215   to the left,  improve=1.6700280, (0 missing)
##       copd              < 0.5    to the right, improve=0.6860574, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6145002, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.5698065, (0 missing)
## 
## Node number 965: 157 observations,    complexity param=0.0008746577
##   predicted class=B2  expected loss=0.5732484  P(node) =0.00785
##     class counts:    49    67    27    12     2
##    probabilities: 0.312 0.427 0.172 0.076 0.013 
##   left son=1930 (28 obs) right son=1931 (129 obs)
##   Primary splits:
##       age        < 88.5   to the right, improve=2.733535, (0 missing)
##       copd       < 0.5    to the left,  improve=2.275853, (0 missing)
##       alzheimers < 0.5    to the left,  improve=1.745083, (0 missing)
##       ihd        < 0.5    to the left,  improve=1.711287, (0 missing)
##       stroke     < 0.5    to the left,  improve=1.709726, (0 missing)
## 
## Node number 966: 74 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.3513514  P(node) =0.0037
##     class counts:    17    48     7     2     0
##    probabilities: 0.230 0.649 0.095 0.027 0.000 
##   left son=1932 (64 obs) right son=1933 (10 obs)
##   Primary splits:
##       reimbursement2008 < 4725   to the left,  improve=2.1494930, (0 missing)
##       age               < 72.5   to the left,  improve=1.9802800, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.4229040, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5439425, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3682432, (0 missing)
## 
## Node number 967: 113 observations,    complexity param=0.000380286
##   predicted class=B2  expected loss=0.5221239  P(node) =0.00565
##     class counts:    34    54    20     5     0
##    probabilities: 0.301 0.478 0.177 0.044 0.000 
##   left son=1934 (9 obs) right son=1935 (104 obs)
##   Primary splits:
##       age               < 78.5   to the left,  improve=2.662942, (0 missing)
##       depression        < 0.5    to the right, improve=2.539583, (0 missing)
##       stroke            < 0.5    to the right, improve=1.321986, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.244120, (0 missing)
##       reimbursement2008 < 4030   to the left,  improve=0.939590, (0 missing)
## 
## Node number 972: 8 observations
##   predicted class=B2  expected loss=0.125  P(node) =0.0004
##     class counts:     1     7     0     0     0
##    probabilities: 0.125 0.875 0.000 0.000 0.000 
## 
## Node number 973: 112 observations,    complexity param=0.0005324004
##   predicted class=B2  expected loss=0.6517857  P(node) =0.0056
##     class counts:    24    39    38    11     0
##    probabilities: 0.214 0.348 0.339 0.098 0.000 
##   left son=1946 (49 obs) right son=1947 (63 obs)
##   Primary splits:
##       age               < 71.5   to the left,  improve=1.734410, (0 missing)
##       reimbursement2008 < 6810   to the left,  improve=1.588784, (0 missing)
##       depression        < 0.5    to the left,  improve=1.542396, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.169209, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.109144, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 24415  to the right, agree=0.58, adj=0.041, (0 split)
## 
## Node number 984: 56 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.625  P(node) =0.0028
##     class counts:    21    20     6     6     3
##    probabilities: 0.375 0.357 0.107 0.107 0.054 
##   left son=1968 (38 obs) right son=1969 (18 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.4889310, (0 missing)
##       age               < 68.5   to the right, improve=2.0304350, (0 missing)
##       reimbursement2008 < 14115  to the left,  improve=1.8107140, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=0.9375588, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5983261, (0 missing)
##   Surrogate splits:
##       age               < 57     to the right, agree=0.714, adj=0.111, (0 split)
##       reimbursement2008 < 60180  to the left,  agree=0.714, adj=0.111, (0 split)
##       bucket2008        < 4.5    to the left,  agree=0.714, adj=0.111, (0 split)
## 
## Node number 985: 127 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.519685  P(node) =0.00635
##     class counts:    31    61    17    17     1
##    probabilities: 0.244 0.480 0.134 0.134 0.008 
##   left son=1970 (85 obs) right son=1971 (42 obs)
##   Primary splits:
##       reimbursement2008 < 6240   to the left,  improve=2.0896490, (0 missing)
##       age               < 67.5   to the left,  improve=1.6822110, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.2999880, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.1106320, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.8561487, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.803, adj=0.405, (0 split)
##       cancer     < 0.5    to the left,  agree=0.685, adj=0.048, (0 split)
## 
## Node number 986: 37 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5945946  P(node) =0.00185
##     class counts:    10    15     5     7     0
##    probabilities: 0.270 0.405 0.135 0.189 0.000 
##   left son=1972 (16 obs) right son=1973 (21 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=1.7162160, (0 missing)
##       age               < 84.5   to the right, improve=1.4384380, (0 missing)
##       copd              < 0.5    to the right, improve=1.2456280, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.0857810, (0 missing)
##       reimbursement2008 < 6875   to the right, improve=0.7102638, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 7200   to the left,  agree=0.703, adj=0.313, (0 split)
##       ihd               < 0.5    to the left,  agree=0.649, adj=0.188, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.649, adj=0.188, (0 split)
##       copd              < 0.5    to the left,  agree=0.595, adj=0.063, (0 split)
## 
## Node number 987: 62 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4032258  P(node) =0.0031
##     class counts:     6    37    16     3     0
##    probabilities: 0.097 0.597 0.258 0.048 0.000 
##   left son=1974 (17 obs) right son=1975 (45 obs)
##   Primary splits:
##       reimbursement2008 < 9010   to the right, improve=1.1586340, (0 missing)
##       age               < 64.5   to the right, improve=0.9974302, (0 missing)
##       cancer            < 0.5    to the right, improve=0.9645161, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5071025, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4342640, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.919, adj=0.706, (0 split)
## 
## Node number 988: 16 observations
##   predicted class=B2  expected loss=0.3125  P(node) =0.0008
##     class counts:     3    11     2     0     0
##    probabilities: 0.188 0.688 0.125 0.000 0.000 
## 
## Node number 989: 225 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.56  P(node) =0.01125
##     class counts:    43    99    60    21     2
##    probabilities: 0.191 0.440 0.267 0.093 0.009 
##   left son=1978 (216 obs) right son=1979 (9 obs)
##   Primary splits:
##       reimbursement2008 < 39120  to the left,  improve=1.9111110, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.5225480, (0 missing)
##       age               < 71.5   to the right, improve=0.9369227, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.9367521, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.7079276, (0 missing)
##   Surrogate splits:
##       bucket2008 < 4.5    to the left,  agree=0.969, adj=0.222, (0 split)
## 
## Node number 992: 67 observations,    complexity param=0.000507048
##   predicted class=B1  expected loss=0.6716418  P(node) =0.00335
##     class counts:    22    18    21     4     2
##    probabilities: 0.328 0.269 0.313 0.060 0.030 
##   left son=1984 (43 obs) right son=1985 (24 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=1.596523, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.434701, (0 missing)
##       reimbursement2008 < 8080   to the left,  improve=1.256193, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.048920, (0 missing)
##       age               < 96.5   to the left,  improve=1.002126, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.672, adj=0.083, (0 split)
##       ihd    < 0.5    to the right, agree=0.657, adj=0.042, (0 split)
## 
## Node number 993: 279 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6344086  P(node) =0.01395
##     class counts:    66   102    50    53     8
##    probabilities: 0.237 0.366 0.179 0.190 0.029 
##   left son=1986 (11 obs) right son=1987 (268 obs)
##   Primary splits:
##       reimbursement2008 < 6780   to the left,  improve=2.133825, (0 missing)
##       age               < 77.5   to the left,  improve=1.516129, (0 missing)
##       stroke            < 0.5    to the right, improve=1.276040, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.116912, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.035800, (0 missing)
## 
## Node number 994: 19 observations
##   predicted class=B2  expected loss=0.2631579  P(node) =0.00095
##     class counts:     3    14     1     1     0
##    probabilities: 0.158 0.737 0.053 0.053 0.000 
## 
## Node number 995: 247 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6153846  P(node) =0.01235
##     class counts:    47    95    67    32     6
##    probabilities: 0.190 0.385 0.271 0.130 0.024 
##   left son=1990 (235 obs) right son=1991 (12 obs)
##   Primary splits:
##       age               < 88.5   to the left,  improve=2.7973120, (0 missing)
##       reimbursement2008 < 6170   to the left,  improve=2.4372470, (0 missing)
##       depression        < 0.5    to the right, improve=0.9399906, (0 missing)
##       ihd               < 0.5    to the right, improve=0.8524106, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.7164122, (0 missing)
## 
## Node number 1002: 107 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.3925234  P(node) =0.00535
##     class counts:    16    65    15    10     1
##    probabilities: 0.150 0.607 0.140 0.093 0.009 
##   left son=2004 (88 obs) right son=2005 (19 obs)
##   Primary splits:
##       reimbursement2008 < 4595   to the left,  improve=1.5568240, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7322522, (0 missing)
##       copd              < 0.5    to the right, improve=0.6210399, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.6176956, (0 missing)
##       age               < 81.5   to the right, improve=0.4955512, (0 missing)
## 
## Node number 1003: 25 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.6  P(node) =0.00125
##     class counts:     4    10     7     4     0
##    probabilities: 0.160 0.400 0.280 0.160 0.000 
##   left son=2006 (16 obs) right son=2007 (9 obs)
##   Primary splits:
##       reimbursement2008 < 4975   to the right, improve=0.9127778, (0 missing)
##       depression        < 0.5    to the left,  improve=0.8119481, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5100000, (0 missing)
##       age               < 66.5   to the right, improve=0.3473016, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.2933333, (0 missing)
##   Surrogate splits:
##       age    < 62.5   to the right, agree=0.80, adj=0.444, (0 split)
##       stroke < 0.5    to the left,  agree=0.68, adj=0.111, (0 split)
## 
## Node number 1004: 16 observations
##   predicted class=B1  expected loss=0.625  P(node) =0.0008
##     class counts:     6     5     3     2     0
##    probabilities: 0.375 0.312 0.188 0.125 0.000 
## 
## Node number 1005: 8 observations
##   predicted class=B3  expected loss=0.375  P(node) =0.0004
##     class counts:     1     2     5     0     0
##    probabilities: 0.125 0.250 0.625 0.000 0.000 
## 
## Node number 1006: 253 observations,    complexity param=0.0002028192
##   predicted class=B2  expected loss=0.5454545  P(node) =0.01265
##     class counts:    29   115    69    35     5
##    probabilities: 0.115 0.455 0.273 0.138 0.020 
##   left son=2012 (35 obs) right son=2013 (218 obs)
##   Primary splits:
##       reimbursement2008 < 6565   to the left,  improve=1.3116340, (0 missing)
##       copd              < 0.5    to the left,  improve=1.0918940, (0 missing)
##       age               < 39     to the left,  improve=0.9539227, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8542281, (0 missing)
##       cancer            < 0.5    to the right, improve=0.8037400, (0 missing)
## 
## Node number 1007: 32 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.375  P(node) =0.0016
##     class counts:     0    20     8     3     1
##    probabilities: 0.000 0.625 0.250 0.094 0.031 
##   left son=2014 (22 obs) right son=2015 (10 obs)
##   Primary splits:
##       reimbursement2008 < 5385   to the right, improve=2.4965910, (0 missing)
##       depression        < 0.5    to the right, improve=1.5511360, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.7271825, (0 missing)
##       age               < 85     to the right, improve=0.5208333, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3541667, (0 missing)
##   Surrogate splits:
##       age < 90.5   to the left,  agree=0.75, adj=0.2, (0 split)
## 
## Node number 1012: 13 observations
##   predicted class=B2  expected loss=0.1538462  P(node) =0.00065
##     class counts:     1    11     0     0     1
##    probabilities: 0.077 0.846 0.000 0.000 0.077 
## 
## Node number 1013: 7 observations
##   predicted class=B4  expected loss=0.4285714  P(node) =0.00035
##     class counts:     0     1     2     4     0
##    probabilities: 0.000 0.143 0.286 0.571 0.000 
## 
## Node number 1016: 95 observations,    complexity param=0.000507048
##   predicted class=B1  expected loss=0.7157895  P(node) =0.00475
##     class counts:    27    23    20    25     0
##    probabilities: 0.284 0.242 0.211 0.263 0.000 
##   left son=2032 (67 obs) right son=2033 (28 obs)
##   Primary splits:
##       reimbursement2008 < 18065  to the right, improve=1.9044550, (0 missing)
##       age               < 86.5   to the left,  improve=1.6124630, (0 missing)
##       bucket2008        < 3.5    to the right, improve=0.8617544, (0 missing)
##       cancer            < 0.5    to the right, improve=0.8550877, (0 missing)
##       stroke            < 0.5    to the right, improve=0.5227689, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.821, adj=0.393, (0 split)
## 
## Node number 1017: 138 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6376812  P(node) =0.0069
##     class counts:    21    50    29    30     8
##    probabilities: 0.152 0.362 0.210 0.217 0.058 
##   left son=2034 (41 obs) right son=2035 (97 obs)
##   Primary splits:
##       reimbursement2008 < 22770  to the right, improve=2.1050500, (0 missing)
##       age               < 73.5   to the left,  improve=1.6683600, (0 missing)
##       stroke            < 0.5    to the right, improve=1.3740260, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.3465420, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9647403, (0 missing)
##   Surrogate splits:
##       age < 40.5   to the left,  agree=0.717, adj=0.049, (0 split)
## 
## Node number 1018: 140 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.5928571  P(node) =0.007
##     class counts:    17    57    38    20     8
##    probabilities: 0.121 0.407 0.271 0.143 0.057 
##   left son=2036 (125 obs) right son=2037 (15 obs)
##   Primary splits:
##       age               < 65     to the right, improve=1.6013330, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.3095240, (0 missing)
##       reimbursement2008 < 16720  to the right, improve=1.2510020, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9871662, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9854436, (0 missing)
## 
## Node number 1019: 23 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.4782609  P(node) =0.00115
##     class counts:     1     5    12     4     1
##    probabilities: 0.043 0.217 0.522 0.174 0.043 
##   left son=2038 (13 obs) right son=2039 (10 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=3.5311040, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.4604740, (0 missing)
##       age               < 79     to the left,  improve=1.2028990, (0 missing)
##       reimbursement2008 < 20175  to the left,  improve=0.3003344, (0 missing)
##       depression        < 0.5    to the right, improve=0.1271410, (0 missing)
##   Surrogate splits:
##       age               < 83.5   to the left,  agree=0.652, adj=0.2, (0 split)
##       cancer            < 0.5    to the left,  agree=0.652, adj=0.2, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.652, adj=0.2, (0 split)
##       reimbursement2008 < 17675  to the left,  agree=0.609, adj=0.1, (0 split)
## 
## Node number 1022: 91 observations,    complexity param=0.0002662002
##   predicted class=B2  expected loss=0.5164835  P(node) =0.00455
##     class counts:     6    44    17    21     3
##    probabilities: 0.066 0.484 0.187 0.231 0.033 
##   left son=2044 (47 obs) right son=2045 (44 obs)
##   Primary splits:
##       age               < 72     to the right, improve=1.4196230, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.2187220, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9937374, (0 missing)
##       stroke            < 0.5    to the right, improve=0.7373929, (0 missing)
##       reimbursement2008 < 31655  to the right, improve=0.7326007, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 27945  to the left,  agree=0.604, adj=0.182, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.582, adj=0.136, (0 split)
##       copd              < 0.5    to the left,  agree=0.571, adj=0.114, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.560, adj=0.091, (0 split)
##       arthritis         < 0.5    to the left,  agree=0.549, adj=0.068, (0 split)
## 
## Node number 1023: 331 observations,    complexity param=0.000507048
##   predicted class=B4  expected loss=0.6827795  P(node) =0.01655
##     class counts:    24   104    80   105    18
##    probabilities: 0.073 0.314 0.242 0.317 0.054 
##   left son=2046 (97 obs) right son=2047 (234 obs)
##   Primary splits:
##       stroke            < 0.5    to the right, improve=1.835692, (0 missing)
##       age               < 34.5   to the left,  improve=1.722335, (0 missing)
##       reimbursement2008 < 52775  to the right, improve=1.679153, (0 missing)
##       bucket2008        < 4.5    to the right, improve=1.290835, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.283171, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 92615  to the right, agree=0.713, adj=0.021, (0 split)
## 
## Node number 1284: 94 observations
##   predicted class=B1  expected loss=0.106383  P(node) =0.0047
##     class counts:    84     5     4     1     0
##    probabilities: 0.894 0.053 0.043 0.011 0.000 
## 
## Node number 1285: 707 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.165488  P(node) =0.03535
##     class counts:   590    68    36    11     2
##    probabilities: 0.835 0.096 0.051 0.016 0.003 
##   left son=2570 (277 obs) right son=2571 (430 obs)
##   Primary splits:
##       reimbursement2008 < 495    to the right, improve=0.7004222, (0 missing)
##       age               < 83.5   to the right, improve=0.4988776, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.3588292, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.3154163, (0 missing)
##       depression        < 0.5    to the left,  improve=0.3116005, (0 missing)
##   Surrogate splits:
##       heart.failure < 0.5    to the right, agree=0.611, adj=0.007, (0 split)
##       ihd           < 0.5    to the right, agree=0.610, adj=0.004, (0 split)
## 
## Node number 1414: 43 observations
##   predicted class=B1  expected loss=0.2790698  P(node) =0.00215
##     class counts:    31     6     3     3     0
##    probabilities: 0.721 0.140 0.070 0.070 0.000 
## 
## Node number 1415: 14 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0007
##     class counts:     5     7     0     2     0
##    probabilities: 0.357 0.500 0.000 0.143 0.000 
## 
## Node number 1420: 9 observations
##   predicted class=B1  expected loss=0.1111111  P(node) =0.00045
##     class counts:     8     0     0     1     0
##    probabilities: 0.889 0.000 0.000 0.111 0.000 
## 
## Node number 1421: 67 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2985075  P(node) =0.00335
##     class counts:    47    16     3     1     0
##    probabilities: 0.701 0.239 0.045 0.015 0.000 
##   left son=2842 (60 obs) right son=2843 (7 obs)
##   Primary splits:
##       age               < 78.5   to the left,  improve=1.4644630, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.8523372, (0 missing)
##       kidney            < 0.5    to the right, improve=0.4113964, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.3161117, (0 missing)
##       reimbursement2008 < 775    to the right, improve=0.2780923, (0 missing)
## 
## Node number 1440: 27 observations
##   predicted class=B1  expected loss=0.07407407  P(node) =0.00135
##     class counts:    25     1     1     0     0
##    probabilities: 0.926 0.037 0.037 0.000 0.000 
## 
## Node number 1441: 256 observations,    complexity param=5.07048e-05
##   predicted class=B1  expected loss=0.2265625  P(node) =0.0128
##     class counts:   198    28    21     9     0
##    probabilities: 0.773 0.109 0.082 0.035 0.000 
##   left son=2882 (197 obs) right son=2883 (59 obs)
##   Primary splits:
##       age               < 80.5   to the left,  improve=1.4661490, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.7479467, (0 missing)
##       reimbursement2008 < 1315   to the right, improve=0.5371438, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4432897, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.3477601, (0 missing)
## 
## Node number 1442: 158 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.2721519  P(node) =0.0079
##     class counts:   115    25    13     5     0
##    probabilities: 0.728 0.158 0.082 0.032 0.000 
##   left son=2884 (109 obs) right son=2885 (49 obs)
##   Primary splits:
##       age               < 73.5   to the right, improve=0.6469703, (0 missing)
##       reimbursement2008 < 1375   to the right, improve=0.4601807, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.3961186, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3805342, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.3789804, (0 missing)
## 
## Node number 1443: 8 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0004
##     class counts:     4     3     1     0     0
##    probabilities: 0.500 0.375 0.125 0.000 0.000 
## 
## Node number 1446: 52 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2884615  P(node) =0.0026
##     class counts:    37    10     2     3     0
##    probabilities: 0.712 0.192 0.038 0.058 0.000 
##   left son=2892 (32 obs) right son=2893 (20 obs)
##   Primary splits:
##       reimbursement2008 < 1155   to the right, improve=1.2875000, (0 missing)
##       age               < 65.5   to the right, improve=0.9991597, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.8375000, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6047619, (0 missing)
##       depression        < 0.5    to the right, improve=0.2711712, (0 missing)
##   Surrogate splits:
##       diabetes   < 0.5    to the left,  agree=0.692, adj=0.20, (0 split)
##       copd       < 0.5    to the left,  agree=0.654, adj=0.10, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.635, adj=0.05, (0 split)
## 
## Node number 1447: 35 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.4285714  P(node) =0.00175
##     class counts:    20    14     1     0     0
##    probabilities: 0.571 0.400 0.029 0.000 0.000 
##   left son=2894 (15 obs) right son=2895 (20 obs)
##   Primary splits:
##       diabetes      < 0.5    to the right, improve=1.7761900, (0 missing)
##       age           < 47.5   to the right, improve=1.5857140, (0 missing)
##       heart.failure < 0.5    to the right, improve=0.5724868, (0 missing)
##       depression    < 0.5    to the left,  improve=0.2257519, (0 missing)
##       alzheimers    < 0.5    to the left,  improve=0.1650794, (0 missing)
##   Surrogate splits:
##       arthritis < 0.5    to the right, agree=0.629, adj=0.133, (0 split)
##       age       < 53.5   to the left,  agree=0.600, adj=0.067, (0 split)
## 
## Node number 1450: 88 observations
##   predicted class=B1  expected loss=0.2954545  P(node) =0.0044
##     class counts:    62    17     5     3     1
##    probabilities: 0.705 0.193 0.057 0.034 0.011 
## 
## Node number 1451: 11 observations
##   predicted class=B2  expected loss=0.4545455  P(node) =0.00055
##     class counts:     3     6     2     0     0
##    probabilities: 0.273 0.545 0.182 0.000 0.000 
## 
## Node number 1474: 145 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.2827586  P(node) =0.00725
##     class counts:   104    25    13     3     0
##    probabilities: 0.717 0.172 0.090 0.021 0.000 
##   left son=2948 (8 obs) right son=2949 (137 obs)
##   Primary splits:
##       age               < 51     to the left,  improve=1.0003520, (0 missing)
##       copd              < 0.5    to the right, improve=0.9153314, (0 missing)
##       reimbursement2008 < 855    to the left,  improve=0.8689655, (0 missing)
##       depression        < 0.5    to the right, improve=0.5758972, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.1184309, (0 missing)
## 
## Node number 1475: 28 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.5357143  P(node) =0.0014
##     class counts:    13     9     4     2     0
##    probabilities: 0.464 0.321 0.143 0.071 0.000 
##   left son=2950 (8 obs) right son=2951 (20 obs)
##   Primary splits:
##       age               < 78.5   to the right, improve=1.607143, (0 missing)
##       reimbursement2008 < 795    to the left,  improve=1.046032, (0 missing)
## 
## Node number 1512: 74 observations
##   predicted class=B1  expected loss=0.2297297  P(node) =0.0037
##     class counts:    57     9     5     3     0
##    probabilities: 0.770 0.122 0.068 0.041 0.000 
## 
## Node number 1513: 139 observations,    complexity param=6.084576e-05
##   predicted class=B1  expected loss=0.3165468  P(node) =0.00695
##     class counts:    95    31    12     0     1
##    probabilities: 0.683 0.223 0.086 0.000 0.007 
##   left son=3026 (14 obs) right son=3027 (125 obs)
##   Primary splits:
##       reimbursement2008 < 1105   to the right, improve=1.4099650, (0 missing)
##       age               < 50.5   to the left,  improve=1.1605620, (0 missing)
##       kidney            < 0.5    to the right, improve=0.6624468, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5567975, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.3267556, (0 missing)
##   Surrogate splits:
##       age < 48     to the left,  agree=0.906, adj=0.071, (0 split)
## 
## Node number 1514: 68 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3382353  P(node) =0.0034
##     class counts:    45    13     5     5     0
##    probabilities: 0.662 0.191 0.074 0.074 0.000 
##   left son=3028 (9 obs) right son=3029 (59 obs)
##   Primary splits:
##       kidney            < 0.5    to the right, improve=1.9792840, (0 missing)
##       reimbursement2008 < 755    to the left,  improve=1.0972640, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.6166667, (0 missing)
##       age               < 67.5   to the left,  improve=0.4893617, (0 missing)
##       depression        < 0.5    to the right, improve=0.4750000, (0 missing)
## 
## Node number 1515: 29 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.5172414  P(node) =0.00145
##     class counts:    14    12     2     1     0
##    probabilities: 0.483 0.414 0.069 0.034 0.000 
##   left son=3030 (20 obs) right son=3031 (9 obs)
##   Primary splits:
##       age               < 83.5   to the right, improve=0.59233720, (0 missing)
##       reimbursement2008 < 805    to the right, improve=0.35900380, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.34587250, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.04029038, (0 missing)
## 
## Node number 1522: 54 observations
##   predicted class=B1  expected loss=0.3703704  P(node) =0.0027
##     class counts:    34    10     6     4     0
##    probabilities: 0.630 0.185 0.111 0.074 0.000 
## 
## Node number 1523: 56 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5535714  P(node) =0.0028
##     class counts:    25    18    11     2     0
##    probabilities: 0.446 0.321 0.196 0.036 0.000 
##   left son=3046 (31 obs) right son=3047 (25 obs)
##   Primary splits:
##       age               < 76.5   to the right, improve=2.6201380, (0 missing)
##       reimbursement2008 < 1225   to the right, improve=1.6819490, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.7819029, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.4322883, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.3928571, (0 missing)
##   Surrogate splits:
##       heart.failure     < 0.5    to the left,  agree=0.714, adj=0.36, (0 split)
##       reimbursement2008 < 1235   to the left,  agree=0.625, adj=0.16, (0 split)
##       kidney            < 0.5    to the left,  agree=0.571, adj=0.04, (0 split)
## 
## Node number 1536: 47 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.2340426  P(node) =0.00235
##     class counts:    36     3     8     0     0
##    probabilities: 0.766 0.064 0.170 0.000 0.000 
##   left son=3072 (40 obs) right son=3073 (7 obs)
##   Primary splits:
##       reimbursement2008 < 1655   to the right, improve=2.2937690, (0 missing)
##       age               < 74.5   to the right, improve=0.9731469, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.5429287, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2009119, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.2009119, (0 missing)
## 
## Node number 1537: 241 observations
##   predicted class=B1  expected loss=0.2821577  P(node) =0.01205
##     class counts:   173    40    20     8     0
##    probabilities: 0.718 0.166 0.083 0.033 0.000 
## 
## Node number 1538: 92 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3369565  P(node) =0.0046
##     class counts:    61    22     7     1     1
##    probabilities: 0.663 0.239 0.076 0.011 0.011 
##   left son=3076 (23 obs) right son=3077 (69 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=0.8695652, (0 missing)
##       reimbursement2008 < 2050   to the right, improve=0.8034579, (0 missing)
##       age               < 48.5   to the right, improve=0.5224638, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2776586, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.2576490, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2545   to the right, agree=0.783, adj=0.13, (0 split)
## 
## Node number 1539: 15 observations
##   predicted class=B1  expected loss=0.6  P(node) =0.00075
##     class counts:     6     5     4     0     0
##    probabilities: 0.400 0.333 0.267 0.000 0.000 
## 
## Node number 1542: 72 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.4027778  P(node) =0.0036
##     class counts:    43    21     6     2     0
##    probabilities: 0.597 0.292 0.083 0.028 0.000 
##   left son=3084 (58 obs) right son=3085 (14 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=1.1709090, (0 missing)
##       reimbursement2008 < 2415   to the left,  improve=1.1055560, (0 missing)
##       age               < 77.5   to the right, improve=0.5181735, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2448002, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.1190754, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2535   to the left,  agree=0.833, adj=0.143, (0 split)
## 
## Node number 1543: 28 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.6071429  P(node) =0.0014
##     class counts:    11     7     5     5     0
##    probabilities: 0.393 0.250 0.179 0.179 0.000 
##   left son=3086 (7 obs) right son=3087 (21 obs)
##   Primary splits:
##       arthritis         < 0.5    to the right, improve=1.3809520, (0 missing)
##       reimbursement2008 < 2070   to the left,  improve=1.1172160, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8539683, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.6925647, (0 missing)
##       age               < 84.5   to the right, improve=0.4345238, (0 missing)
##   Surrogate splits:
##       age < 82.5   to the left,  agree=0.786, adj=0.143, (0 split)
## 
## Node number 1556: 41 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.4146341  P(node) =0.00205
##     class counts:    24    17     0     0     0
##    probabilities: 0.585 0.415 0.000 0.000 0.000 
##   left son=3112 (30 obs) right son=3113 (11 obs)
##   Primary splits:
##       reimbursement2008 < 2765   to the right, improve=1.4781970, (0 missing)
##       age               < 77.5   to the left,  improve=1.4649390, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.4224390, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.5474390, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4579946, (0 missing)
## 
## Node number 1557: 25 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.4  P(node) =0.00125
##     class counts:    15     6     3     0     1
##    probabilities: 0.600 0.240 0.120 0.000 0.040 
##   left son=3114 (18 obs) right son=3115 (7 obs)
##   Primary splits:
##       reimbursement2008 < 3090   to the left,  improve=2.2711110, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=2.0933330, (0 missing)
##       age               < 89.5   to the left,  improve=0.4139683, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.3405556, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.88, adj=0.571, (0 split)
##       diabetes   < 0.5    to the left,  agree=0.80, adj=0.286, (0 split)
##       age        < 93.5   to the left,  agree=0.76, adj=0.143, (0 split)
## 
## Node number 1580: 26 observations
##   predicted class=B1  expected loss=0.3461538  P(node) =0.0013
##     class counts:    17     7     1     0     1
##    probabilities: 0.654 0.269 0.038 0.000 0.038 
## 
## Node number 1581: 24 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.5833333  P(node) =0.0012
##     class counts:    10     9     1     4     0
##    probabilities: 0.417 0.375 0.042 0.167 0.000 
##   left son=3162 (17 obs) right son=3163 (7 obs)
##   Primary splits:
##       age               < 68.5   to the left,  improve=1.2794120, (0 missing)
##       reimbursement2008 < 1855   to the right, improve=1.1785710, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4054622, (0 missing)
## 
## Node number 1590: 113 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5486726  P(node) =0.00565
##     class counts:    51    37    21     3     1
##    probabilities: 0.451 0.327 0.186 0.027 0.009 
##   left son=3180 (8 obs) right son=3181 (105 obs)
##   Primary splits:
##       reimbursement2008 < 3055   to the right, improve=2.8499160, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.9081570, (0 missing)
##       arthritis         < 0.5    to the right, improve=1.0615610, (0 missing)
##       age               < 75.5   to the right, improve=1.0498240, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7734827, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the right, agree=0.991, adj=0.875, (0 split)
## 
## Node number 1591: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     1     5     2     0     0
##    probabilities: 0.125 0.625 0.250 0.000 0.000 
## 
## Node number 1666: 86 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.3604651  P(node) =0.0043
##     class counts:    55    19     7     4     1
##    probabilities: 0.640 0.221 0.081 0.047 0.012 
##   left son=3332 (70 obs) right son=3333 (16 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=2.3426080, (0 missing)
##       age               < 91.5   to the right, improve=1.6553370, (0 missing)
##       copd              < 0.5    to the left,  improve=1.0437260, (0 missing)
##       reimbursement2008 < 2295   to the left,  improve=1.0350680, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4926252, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1585   to the right, agree=0.849, adj=0.187, (0 split)
## 
## Node number 1667: 58 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.5  P(node) =0.0029
##     class counts:    29    24     3     2     0
##    probabilities: 0.500 0.414 0.052 0.034 0.000 
##   left son=3334 (8 obs) right son=3335 (50 obs)
##   Primary splits:
##       age               < 75.5   to the left,  improve=1.4148280, (0 missing)
##       reimbursement2008 < 2375   to the left,  improve=0.6389452, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3897888, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.3122694, (0 missing)
##       copd              < 0.5    to the left,  improve=0.2848276, (0 missing)
## 
## Node number 1670: 63 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.5079365  P(node) =0.00315
##     class counts:    31    27     4     0     1
##    probabilities: 0.492 0.429 0.063 0.000 0.016 
##   left son=3340 (33 obs) right son=3341 (30 obs)
##   Primary splits:
##       reimbursement2008 < 2015   to the left,  improve=1.6441560, (0 missing)
##       age               < 87.5   to the left,  improve=1.0505420, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5047619, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3234222, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.1904762, (0 missing)
##   Surrogate splits:
##       age           < 84.5   to the left,  agree=0.651, adj=0.267, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.619, adj=0.200, (0 split)
##       osteoporosis  < 0.5    to the left,  agree=0.603, adj=0.167, (0 split)
##       kidney        < 0.5    to the left,  agree=0.556, adj=0.067, (0 split)
## 
## Node number 1671: 25 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.52  P(node) =0.00125
##     class counts:    12     6     2     5     0
##    probabilities: 0.480 0.240 0.080 0.200 0.000 
##   left son=3342 (10 obs) right son=3343 (15 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=2.8400000, (0 missing)
##       age               < 83     to the left,  improve=1.6400000, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.2893510, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.2400000, (0 missing)
##       reimbursement2008 < 2250   to the right, improve=0.3964103, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1705   to the left,  agree=0.72, adj=0.3, (0 split)
## 
## Node number 1672: 218 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.3899083  P(node) =0.0109
##     class counts:   133    56    18    10     1
##    probabilities: 0.610 0.257 0.083 0.046 0.005 
##   left son=3344 (211 obs) right son=3345 (7 obs)
##   Primary splits:
##       reimbursement2008 < 2485   to the left,  improve=2.3387790, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.3542280, (0 missing)
##       age               < 65.5   to the left,  improve=1.2410730, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3575472, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3120983, (0 missing)
## 
## Node number 1673: 10 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0005
##     class counts:     2     5     2     1     0
##    probabilities: 0.200 0.500 0.200 0.100 0.000 
## 
## Node number 1674: 26 observations,    complexity param=0.000380286
##   predicted class=B2  expected loss=0.6153846  P(node) =0.0013
##     class counts:     9    10     3     4     0
##    probabilities: 0.346 0.385 0.115 0.154 0.000 
##   left son=3348 (18 obs) right son=3349 (8 obs)
##   Primary splits:
##       age               < 54.5   to the right, improve=1.24359000, (0 missing)
##       reimbursement2008 < 1790   to the right, improve=1.21978000, (0 missing)
##       copd              < 0.5    to the left,  improve=0.92692310, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.88247860, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.04055944, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1620   to the right, agree=0.769, adj=0.25, (0 split)
## 
## Node number 1675: 7 observations
##   predicted class=B3  expected loss=0.2857143  P(node) =0.00035
##     class counts:     0     2     5     0     0
##    probabilities: 0.000 0.286 0.714 0.000 0.000 
## 
## Node number 1676: 115 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.5826087  P(node) =0.00575
##     class counts:    48    46    11     8     2
##    probabilities: 0.417 0.400 0.096 0.070 0.017 
##   left son=3352 (98 obs) right son=3353 (17 obs)
##   Primary splits:
##       age               < 55.5   to the right, improve=1.4583540, (0 missing)
##       reimbursement2008 < 2165   to the left,  improve=1.1979300, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.7250725, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7110961, (0 missing)
##       kidney            < 0.5    to the right, improve=0.5440382, (0 missing)
## 
## Node number 1677: 31 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.516129  P(node) =0.00155
##     class counts:     8    15     8     0     0
##    probabilities: 0.258 0.484 0.258 0.000 0.000 
##   left son=3354 (23 obs) right son=3355 (8 obs)
##   Primary splits:
##       age               < 62     to the right, improve=1.4824680, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.0802950, (0 missing)
##       reimbursement2008 < 2375   to the right, improve=0.9813243, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.4108830, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.3776091, (0 missing)
## 
## Node number 1678: 11 observations
##   predicted class=B1  expected loss=0.4545455  P(node) =0.00055
##     class counts:     6     4     1     0     0
##    probabilities: 0.545 0.364 0.091 0.000 0.000 
## 
## Node number 1679: 25 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.64  P(node) =0.00125
##     class counts:     9     3     9     3     1
##    probabilities: 0.360 0.120 0.360 0.120 0.040 
##   left son=3358 (8 obs) right son=3359 (17 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=1.0982350, (0 missing)
##       reimbursement2008 < 1975   to the right, improve=1.0805130, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.8988889, (0 missing)
##       age               < 62     to the right, improve=0.7600000, (0 missing)
##       kidney            < 0.5    to the right, improve=0.3850000, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1680   to the left,  agree=0.76, adj=0.250, (0 split)
##       arthritis         < 0.5    to the right, agree=0.72, adj=0.125, (0 split)
## 
## Node number 1712: 62 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.3225806  P(node) =0.0031
##     class counts:    42    11     4     4     1
##    probabilities: 0.677 0.177 0.065 0.065 0.016 
##   left son=3424 (28 obs) right son=3425 (34 obs)
##   Primary splits:
##       heart.failure < 0.5    to the right, improve=1.6485500, (0 missing)
##       arthritis     < 0.5    to the left,  improve=0.7549923, (0 missing)
##       diabetes      < 0.5    to the left,  improve=0.7121352, (0 missing)
##       age           < 65.5   to the right, improve=0.6478495, (0 missing)
##       kidney        < 0.5    to the left,  improve=0.6010580, (0 missing)
##   Surrogate splits:
##       age               < 64.5   to the left,  agree=0.629, adj=0.179, (0 split)
##       reimbursement2008 < 1640   to the left,  agree=0.629, adj=0.179, (0 split)
##       arthritis         < 0.5    to the right, agree=0.581, adj=0.071, (0 split)
##       osteoporosis      < 0.5    to the right, agree=0.581, adj=0.071, (0 split)
## 
## Node number 1713: 14 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0007
##     class counts:     6     7     0     1     0
##    probabilities: 0.429 0.500 0.000 0.071 0.000 
## 
## Node number 1714: 54 observations,    complexity param=0.0004563432
##   predicted class=B1  expected loss=0.6111111  P(node) =0.0027
##     class counts:    21    17    12     4     0
##    probabilities: 0.389 0.315 0.222 0.074 0.000 
##   left son=3428 (25 obs) right son=3429 (29 obs)
##   Primary splits:
##       reimbursement2008 < 2305   to the right, improve=1.9598980, (0 missing)
##       kidney            < 0.5    to the right, improve=0.8518519, (0 missing)
##       age               < 47.5   to the left,  improve=0.7033011, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6296296, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.4470899, (0 missing)
##   Surrogate splits:
##       age          < 67.5   to the left,  agree=0.593, adj=0.12, (0 split)
##       kidney       < 0.5    to the right, agree=0.593, adj=0.12, (0 split)
##       osteoporosis < 0.5    to the left,  agree=0.574, adj=0.08, (0 split)
##       copd         < 0.5    to the right, agree=0.556, adj=0.04, (0 split)
##       diabetes     < 0.5    to the left,  agree=0.556, adj=0.04, (0 split)
## 
## Node number 1715: 32 observations
##   predicted class=B2  expected loss=0.4375  P(node) =0.0016
##     class counts:     7    18     4     3     0
##    probabilities: 0.219 0.562 0.125 0.094 0.000 
## 
## Node number 1716: 8 observations
##   predicted class=B1  expected loss=0.375  P(node) =0.0004
##     class counts:     5     2     1     0     0
##    probabilities: 0.625 0.250 0.125 0.000 0.000 
## 
## Node number 1717: 109 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.4678899  P(node) =0.00545
##     class counts:    34    58    16     1     0
##    probabilities: 0.312 0.532 0.147 0.009 0.000 
##   left son=3434 (10 obs) right son=3435 (99 obs)
##   Primary splits:
##       reimbursement2008 < 2375   to the right, improve=1.1662310, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.6716092, (0 missing)
##       age               < 77.5   to the right, improve=0.6449413, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.4027486, (0 missing)
##       copd              < 0.5    to the right, improve=0.3923570, (0 missing)
## 
## Node number 1730: 37 observations
##   predicted class=B1  expected loss=0.4054054  P(node) =0.00185
##     class counts:    22    10     3     2     0
##    probabilities: 0.595 0.270 0.081 0.054 0.000 
## 
## Node number 1731: 10 observations
##   predicted class=B2  expected loss=0.4  P(node) =0.0005
##     class counts:     4     6     0     0     0
##    probabilities: 0.400 0.600 0.000 0.000 0.000 
## 
## Node number 1732: 23 observations
##   predicted class=B1  expected loss=0.173913  P(node) =0.00115
##     class counts:    19     2     2     0     0
##    probabilities: 0.826 0.087 0.087 0.000 0.000 
## 
## Node number 1733: 69 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4492754  P(node) =0.00345
##     class counts:    38    19     8     4     0
##    probabilities: 0.551 0.275 0.116 0.058 0.000 
##   left son=3466 (14 obs) right son=3467 (55 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the right, improve=1.5175230, (0 missing)
##       age               < 83.5   to the left,  improve=1.3893230, (0 missing)
##       copd              < 0.5    to the left,  improve=1.2426350, (0 missing)
##       reimbursement2008 < 2575   to the right, improve=0.9229627, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.3642763, (0 missing)
## 
## Node number 1734: 104 observations,    complexity param=0.0002662002
##   predicted class=B1  expected loss=0.5192308  P(node) =0.0052
##     class counts:    50    29    19     4     2
##    probabilities: 0.481 0.279 0.183 0.038 0.019 
##   left son=3468 (58 obs) right son=3469 (46 obs)
##   Primary splits:
##       age               < 79.5   to the left,  improve=2.1095890, (0 missing)
##       reimbursement2008 < 2985   to the right, improve=0.9038462, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7115385, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.6589459, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.5448718, (0 missing)
##   Surrogate splits:
##       depression < 0.5    to the left,  agree=0.577, adj=0.043, (0 split)
## 
## Node number 1735: 17 observations
##   predicted class=B2  expected loss=0.4117647  P(node) =0.00085
##     class counts:     3    10     3     1     0
##    probabilities: 0.176 0.588 0.176 0.059 0.000 
## 
## Node number 1744: 8 observations
##   predicted class=B1  expected loss=0.125  P(node) =0.0004
##     class counts:     7     1     0     0     0
##    probabilities: 0.875 0.125 0.000 0.000 0.000 
## 
## Node number 1745: 125 observations,    complexity param=0.0006084576
##   predicted class=B1  expected loss=0.552  P(node) =0.00625
##     class counts:    56    47    11    11     0
##    probabilities: 0.448 0.376 0.088 0.088 0.000 
##   left son=3490 (67 obs) right son=3491 (58 obs)
##   Primary splits:
##       reimbursement2008 < 2925   to the left,  improve=2.8552090, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=1.9365760, (0 missing)
##       age               < 69.5   to the right, improve=1.3716470, (0 missing)
##       depression        < 0.5    to the left,  improve=1.2843600, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.7595364, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.920, adj=0.828, (0 split)
##       age        < 68.5   to the right, agree=0.560, adj=0.052, (0 split)
##       cancer     < 0.5    to the left,  agree=0.544, adj=0.017, (0 split)
##       depression < 0.5    to the left,  agree=0.544, adj=0.017, (0 split)
## 
## Node number 1750: 10 observations
##   predicted class=B2  expected loss=0.3  P(node) =0.0005
##     class counts:     1     7     1     1     0
##    probabilities: 0.100 0.700 0.100 0.100 0.000 
## 
## Node number 1751: 46 observations,    complexity param=0.0003549336
##   predicted class=B2  expected loss=0.6956522  P(node) =0.0023
##     class counts:    12    14    13     7     0
##    probabilities: 0.261 0.304 0.283 0.152 0.000 
##   left son=3502 (39 obs) right son=3503 (7 obs)
##   Primary splits:
##       reimbursement2008 < 2845   to the right, improve=1.2541810, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7267081, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=0.6921773, (0 missing)
##       age               < 79.5   to the left,  improve=0.6284938, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6278986, (0 missing)
## 
## Node number 1760: 104 observations,    complexity param=0.0002788764
##   predicted class=B2  expected loss=0.5480769  P(node) =0.0052
##     class counts:    38    47    14     4     1
##    probabilities: 0.365 0.452 0.135 0.038 0.010 
##   left son=3520 (40 obs) right son=3521 (64 obs)
##   Primary splits:
##       reimbursement2008 < 2785   to the right, improve=0.8831731, (0 missing)
##       age               < 44.5   to the right, improve=0.5618273, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4772990, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.4681073, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4366792, (0 missing)
##   Surrogate splits:
##       age < 66.5   to the left,  agree=0.673, adj=0.15, (0 split)
## 
## Node number 1761: 38 observations,    complexity param=0.0002788764
##   predicted class=B2  expected loss=0.6315789  P(node) =0.0019
##     class counts:    11    14    13     0     0
##    probabilities: 0.289 0.368 0.342 0.000 0.000 
##   left son=3522 (12 obs) right son=3523 (26 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the right, improve=2.018219, (0 missing)
##       copd              < 0.5    to the left,  improve=1.710526, (0 missing)
##       reimbursement2008 < 2585   to the right, improve=1.660526, (0 missing)
##       age               < 67     to the left,  improve=1.530526, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.453383, (0 missing)
##   Surrogate splits:
##       age               < 49     to the left,  agree=0.789, adj=0.333, (0 split)
##       depression        < 0.5    to the right, agree=0.711, adj=0.083, (0 split)
##       reimbursement2008 < 2535   to the left,  agree=0.711, adj=0.083, (0 split)
## 
## Node number 1776: 11 observations
##   predicted class=B2  expected loss=0.3636364  P(node) =0.00055
##     class counts:     3     7     1     0     0
##    probabilities: 0.273 0.636 0.091 0.000 0.000 
## 
## Node number 1777: 29 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.5172414  P(node) =0.00145
##     class counts:    14     9     4     1     1
##    probabilities: 0.483 0.310 0.138 0.034 0.034 
##   left son=3554 (11 obs) right son=3555 (18 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=2.6659700, (0 missing)
##       age               < 70.5   to the left,  improve=1.7117970, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.7085386, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.6760711, (0 missing)
##       reimbursement2008 < 3195   to the right, improve=0.4333554, (0 missing)
##   Surrogate splits:
##       depression        < 0.5    to the left,  agree=0.69, adj=0.182, (0 split)
##       reimbursement2008 < 3105   to the left,  agree=0.69, adj=0.182, (0 split)
## 
## Node number 1794: 64 observations
##   predicted class=B1  expected loss=0.265625  P(node) =0.0032
##     class counts:    47    10     4     3     0
##    probabilities: 0.734 0.156 0.062 0.047 0.000 
## 
## Node number 1795: 30 observations,    complexity param=0.0001014096
##   predicted class=B1  expected loss=0.4666667  P(node) =0.0015
##     class counts:    16    10     3     1     0
##    probabilities: 0.533 0.333 0.100 0.033 0.000 
##   left son=3590 (23 obs) right son=3591 (7 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=1.1043480, (0 missing)
##       age               < 78.5   to the left,  improve=0.6035714, (0 missing)
##       reimbursement2008 < 4575   to the right, improve=0.2593301, (0 missing)
##       kidney            < 0.5    to the right, improve=0.1863636, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 7295   to the left,  agree=0.833, adj=0.286, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.833, adj=0.286, (0 split)
## 
## Node number 1796: 22 observations
##   predicted class=B1  expected loss=0.1363636  P(node) =0.0011
##     class counts:    19     2     1     0     0
##    probabilities: 0.864 0.091 0.045 0.000 0.000 
## 
## Node number 1797: 67 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.4328358  P(node) =0.00335
##     class counts:    38    19     6     3     1
##    probabilities: 0.567 0.284 0.090 0.045 0.015 
##   left son=3594 (56 obs) right son=3595 (11 obs)
##   Primary splits:
##       reimbursement2008 < 10695  to the right, improve=1.6978100, (0 missing)
##       age               < 79.5   to the left,  improve=1.5082190, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.4828650, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.8686780, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6091704, (0 missing)
##   Surrogate splits:
##       age < 51.5   to the right, agree=0.851, adj=0.091, (0 split)
## 
## Node number 1798: 105 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.4380952  P(node) =0.00525
##     class counts:    59    27    17     2     0
##    probabilities: 0.562 0.257 0.162 0.019 0.000 
##   left son=3596 (8 obs) right son=3597 (97 obs)
##   Primary splits:
##       age               < 88.5   to the right, improve=1.2302650, (0 missing)
##       reimbursement2008 < 5125   to the right, improve=1.1629710, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8149030, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.6619048, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.3031746, (0 missing)
## 
## Node number 1799: 16 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0008
##     class counts:     2     8     4     1     1
##    probabilities: 0.125 0.500 0.250 0.062 0.062 
## 
## Node number 1804: 26 observations
##   predicted class=B1  expected loss=0.3461538  P(node) =0.0013
##     class counts:    17     7     2     0     0
##    probabilities: 0.654 0.269 0.077 0.000 0.000 
## 
## Node number 1805: 34 observations,    complexity param=0.0003549336
##   predicted class=B2  expected loss=0.5294118  P(node) =0.0017
##     class counts:    13    16     3     2     0
##    probabilities: 0.382 0.471 0.088 0.059 0.000 
##   left son=3610 (22 obs) right son=3611 (12 obs)
##   Primary splits:
##       age               < 83.5   to the left,  improve=1.2843140, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5294118, (0 missing)
##       reimbursement2008 < 8165   to the right, improve=0.4298164, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.4298164, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.3587538, (0 missing)
##   Surrogate splits:
##       kidney            < 0.5    to the left,  agree=0.735, adj=0.250, (0 split)
##       reimbursement2008 < 9210   to the left,  agree=0.735, adj=0.250, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.676, adj=0.083, (0 split)
## 
## Node number 1822: 22 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5  P(node) =0.0011
##     class counts:     7    11     3     1     0
##    probabilities: 0.318 0.500 0.136 0.045 0.000 
##   left son=3644 (7 obs) right son=3645 (15 obs)
##   Primary splits:
##       reimbursement2008 < 14605  to the left,  improve=1.8372290, (0 missing)
##       copd              < 0.5    to the right, improve=0.6045066, (0 missing)
##       age               < 83.5   to the left,  improve=0.5454545, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4658009, (0 missing)
##       bucket2008        < 3.5    to the right, improve=0.4181818, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the left,  agree=0.773, adj=0.286, (0 split)
##       age        < 77     to the left,  agree=0.727, adj=0.143, (0 split)
## 
## Node number 1823: 32 observations,    complexity param=0.0003549336
##   predicted class=B3  expected loss=0.59375  P(node) =0.0016
##     class counts:    11     7    13     1     0
##    probabilities: 0.344 0.219 0.406 0.031 0.000 
##   left son=3646 (9 obs) right son=3647 (23 obs)
##   Primary splits:
##       copd              < 0.5    to the right, improve=1.4619570, (0 missing)
##       reimbursement2008 < 7995   to the left,  improve=1.1931820, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.1931820, (0 missing)
##       age               < 77.5   to the right, improve=0.7692857, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.6765873, (0 missing)
##   Surrogate splits:
##       kidney < 0.5    to the right, agree=0.812, adj=0.333, (0 split)
##       stroke < 0.5    to the right, agree=0.812, adj=0.333, (0 split)
## 
## Node number 1828: 18 observations
##   predicted class=B1  expected loss=0.3888889  P(node) =0.0009
##     class counts:    11     3     0     4     0
##    probabilities: 0.611 0.167 0.000 0.222 0.000 
## 
## Node number 1829: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     2     4     0     1     0
##    probabilities: 0.286 0.571 0.000 0.143 0.000 
## 
## Node number 1872: 11 observations
##   predicted class=B2  expected loss=0.4545455  P(node) =0.00055
##     class counts:     5     6     0     0     0
##    probabilities: 0.455 0.545 0.000 0.000 0.000 
## 
## Node number 1873: 16 observations
##   predicted class=B1  expected loss=0.3125  P(node) =0.0008
##     class counts:    11     2     2     1     0
##    probabilities: 0.688 0.125 0.125 0.062 0.000 
## 
## Node number 1874: 7 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.00035
##     class counts:     4     2     1     0     0
##    probabilities: 0.571 0.286 0.143 0.000 0.000 
## 
## Node number 1875: 38 observations,    complexity param=7.60572e-05
##   predicted class=B2  expected loss=0.3684211  P(node) =0.0019
##     class counts:     8    24     4     2     0
##    probabilities: 0.211 0.632 0.105 0.053 0.000 
##   left son=3750 (13 obs) right son=3751 (25 obs)
##   Primary splits:
##       reimbursement2008 < 4175   to the left,  improve=1.2469640, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3250655, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.3030075, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2482456, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.2387218, (0 missing)
##   Surrogate splits:
##       age          < 58.5   to the left,  agree=0.711, adj=0.154, (0 split)
##       osteoporosis < 0.5    to the right, agree=0.711, adj=0.154, (0 split)
## 
## Node number 1878: 13 observations
##   predicted class=B2  expected loss=0.3076923  P(node) =0.00065
##     class counts:     2     9     1     1     0
##    probabilities: 0.154 0.692 0.077 0.077 0.000 
## 
## Node number 1879: 39 observations,    complexity param=0.0003549336
##   predicted class=B3  expected loss=0.6410256  P(node) =0.00195
##     class counts:     9    13    14     3     0
##    probabilities: 0.231 0.333 0.359 0.077 0.000 
##   left son=3758 (25 obs) right son=3759 (14 obs)
##   Primary splits:
##       reimbursement2008 < 5860   to the right, improve=2.5504760, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.1111110, (0 missing)
##       age               < 69.5   to the right, improve=1.0712640, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.7000000, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.6969697, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.795, adj=0.429, (0 split)
##       age        < 68.5   to the right, agree=0.769, adj=0.357, (0 split)
## 
## Node number 1882: 26 observations
##   predicted class=B1  expected loss=0.5769231  P(node) =0.0013
##     class counts:    11     5     5     5     0
##    probabilities: 0.423 0.192 0.192 0.192 0.000 
## 
## Node number 1883: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     1     2     4     0     0
##    probabilities: 0.143 0.286 0.571 0.000 0.000 
## 
## Node number 1912: 30 observations,    complexity param=0.000253524
##   predicted class=B1  expected loss=0.6333333  P(node) =0.0015
##     class counts:    11    11     5     3     0
##    probabilities: 0.367 0.367 0.167 0.100 0.000 
##   left son=3824 (15 obs) right son=3825 (15 obs)
##   Primary splits:
##       age               < 68.5   to the right, improve=1.4666670, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.0009570, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9900452, (0 missing)
##       reimbursement2008 < 7610   to the right, improve=0.7130435, (0 missing)
##       kidney            < 0.5    to the right, improve=0.5222222, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 6645   to the left,  agree=0.667, adj=0.333, (0 split)
##       alzheimers        < 0.5    to the right, agree=0.600, adj=0.200, (0 split)
##       arthritis         < 0.5    to the left,  agree=0.533, adj=0.067, (0 split)
##       cancer            < 0.5    to the right, agree=0.533, adj=0.067, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.533, adj=0.067, (0 split)
## 
## Node number 1913: 11 observations
##   predicted class=B2  expected loss=0.5454545  P(node) =0.00055
##     class counts:     0     5     5     1     0
##    probabilities: 0.000 0.455 0.455 0.091 0.000 
## 
## Node number 1914: 31 observations
##   predicted class=B2  expected loss=0.4193548  P(node) =0.00155
##     class counts:     3    18     8     2     0
##    probabilities: 0.097 0.581 0.258 0.065 0.000 
## 
## Node number 1915: 7 observations
##   predicted class=B3  expected loss=0.2857143  P(node) =0.00035
##     class counts:     1     1     5     0     0
##    probabilities: 0.143 0.143 0.714 0.000 0.000 
## 
## Node number 1920: 32 observations,    complexity param=0.0003422574
##   predicted class=B1  expected loss=0.53125  P(node) =0.0016
##     class counts:    15    15     2     0     0
##    probabilities: 0.469 0.469 0.062 0.000 0.000 
##   left son=3840 (8 obs) right son=3841 (24 obs)
##   Primary splits:
##       age               < 57.5   to the left,  improve=0.8125000, (0 missing)
##       reimbursement2008 < 7940   to the right, improve=0.7690217, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.7690217, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.7034091, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3958333, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 8620   to the right, agree=0.812, adj=0.25, (0 split)
## 
## Node number 1921: 123 observations,    complexity param=0.0003422574
##   predicted class=B1  expected loss=0.495935  P(node) =0.00615
##     class counts:    62    32    26     3     0
##    probabilities: 0.504 0.260 0.211 0.024 0.000 
##   left son=3842 (19 obs) right son=3843 (104 obs)
##   Primary splits:
##       reimbursement2008 < 5150   to the right, improve=2.8759260, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.1396420, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6208037, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4917080, (0 missing)
##       age               < 59.5   to the left,  improve=0.4634146, (0 missing)
##   Surrogate splits:
##       age < 32.5   to the left,  agree=0.862, adj=0.105, (0 split)
## 
## Node number 1924: 31 observations,    complexity param=0.000507048
##   predicted class=B1  expected loss=0.6129032  P(node) =0.00155
##     class counts:    12    11     2     5     1
##    probabilities: 0.387 0.355 0.065 0.161 0.032 
##   left son=3848 (7 obs) right son=3849 (24 obs)
##   Primary splits:
##       age               < 67.5   to the right, improve=2.6862520, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9410138, (0 missing)
##       reimbursement2008 < 24480  to the left,  improve=0.8052995, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.6933948, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.4838710, (0 missing)
## 
## Node number 1925: 21 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.6666667  P(node) =0.00105
##     class counts:     4     5     7     5     0
##    probabilities: 0.190 0.238 0.333 0.238 0.000 
##   left son=3850 (13 obs) right son=3851 (8 obs)
##   Primary splits:
##       age               < 56.5   to the right, improve=0.8507326, (0 missing)
##       reimbursement2008 < 16675  to the left,  improve=0.6692641, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5815018, (0 missing)
##       bucket2008        < 3.5    to the right, improve=0.4853480, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4682540, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 16065  to the right, agree=0.667, adj=0.125, (0 split)
## 
## Node number 1926: 15 observations
##   predicted class=B1  expected loss=0.6  P(node) =0.00075
##     class counts:     6     3     5     1     0
##    probabilities: 0.400 0.200 0.333 0.067 0.000 
## 
## Node number 1927: 11 observations
##   predicted class=B3  expected loss=0.4545455  P(node) =0.00055
##     class counts:     2     0     6     3     0
##    probabilities: 0.182 0.000 0.545 0.273 0.000 
## 
## Node number 1928: 144 observations,    complexity param=0.0004563432
##   predicted class=B1  expected loss=0.5069444  P(node) =0.0072
##     class counts:    71    49    15     9     0
##    probabilities: 0.493 0.340 0.104 0.063 0.000 
##   left son=3856 (117 obs) right son=3857 (27 obs)
##   Primary splits:
##       age               < 73.5   to the right, improve=1.6075500, (0 missing)
##       reimbursement2008 < 5230   to the left,  improve=1.4092590, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6035354, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.5234020, (0 missing)
##       copd              < 0.5    to the right, improve=0.3870370, (0 missing)
## 
## Node number 1929: 26 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6538462  P(node) =0.0013
##     class counts:     7     9     8     1     1
##    probabilities: 0.269 0.346 0.308 0.038 0.038 
##   left son=3858 (7 obs) right son=3859 (19 obs)
##   Primary splits:
##       age               < 92.5   to the right, improve=1.7397340, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.4865380, (0 missing)
##       reimbursement2008 < 13275  to the left,  improve=1.1004270, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7115385, (0 missing)
##       copd              < 0.5    to the right, improve=0.6153846, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 5905   to the left,  agree=0.769, adj=0.143, (0 split)
## 
## Node number 1930: 28 observations,    complexity param=0.0006084576
##   predicted class=B1  expected loss=0.4642857  P(node) =0.0014
##     class counts:    15     9     1     2     1
##    probabilities: 0.536 0.321 0.036 0.071 0.036 
##   left son=3860 (17 obs) right son=3861 (11 obs)
##   Primary splits:
##       age               < 94.5   to the left,  improve=3.2207790, (0 missing)
##       reimbursement2008 < 15610  to the left,  improve=1.3333330, (0 missing)
##       copd              < 0.5    to the left,  improve=1.1488100, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.0091900, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7619048, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 18790  to the left,  agree=0.679, adj=0.182, (0 split)
##       bucket2008        < 3.5    to the left,  agree=0.679, adj=0.182, (0 split)
## 
## Node number 1931: 129 observations,    complexity param=0.0004056384
##   predicted class=B2  expected loss=0.5503876  P(node) =0.00645
##     class counts:    34    58    26    10     1
##    probabilities: 0.264 0.450 0.202 0.078 0.008 
##   left son=3862 (61 obs) right son=3863 (68 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=2.320337, (0 missing)
##       copd              < 0.5    to the left,  improve=1.845030, (0 missing)
##       reimbursement2008 < 6885   to the right, improve=1.627912, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.372989, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.116088, (0 missing)
##   Surrogate splits:
##       age               < 82.5   to the right, agree=0.597, adj=0.148, (0 split)
##       reimbursement2008 < 14610  to the left,  agree=0.566, adj=0.082, (0 split)
##       bucket2008        < 3.5    to the left,  agree=0.566, adj=0.082, (0 split)
##       ihd               < 0.5    to the left,  agree=0.535, adj=0.016, (0 split)
## 
## Node number 1932: 64 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.40625  P(node) =0.0032
##     class counts:    17    38     7     2     0
##    probabilities: 0.266 0.594 0.109 0.031 0.000 
##   left son=3864 (50 obs) right son=3865 (14 obs)
##   Primary splits:
##       reimbursement2008 < 4345   to the left,  improve=4.173750, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.653328, (0 missing)
##       age               < 72.5   to the left,  improve=1.548721, (0 missing)
##       depression        < 0.5    to the left,  improve=0.793750, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.494532, (0 missing)
## 
## Node number 1933: 10 observations
##   predicted class=B2  expected loss=0  P(node) =0.0005
##     class counts:     0    10     0     0     0
##    probabilities: 0.000 1.000 0.000 0.000 0.000 
## 
## Node number 1934: 9 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.00045
##     class counts:     6     1     2     0     0
##    probabilities: 0.667 0.111 0.222 0.000 0.000 
## 
## Node number 1935: 104 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.4903846  P(node) =0.0052
##     class counts:    28    53    18     5     0
##    probabilities: 0.269 0.510 0.173 0.048 0.000 
##   left son=3870 (37 obs) right son=3871 (67 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=1.7427860, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.3422740, (0 missing)
##       stroke            < 0.5    to the right, improve=1.1791950, (0 missing)
##       reimbursement2008 < 4030   to the left,  improve=1.0517090, (0 missing)
##       age               < 80.5   to the left,  improve=0.6396844, (0 missing)
##   Surrogate splits:
##       stroke < 0.5    to the right, agree=0.654, adj=0.027, (0 split)
## 
## Node number 1946: 49 observations,    complexity param=0.0005324004
##   predicted class=B1  expected loss=0.6734694  P(node) =0.00245
##     class counts:    16    13    16     4     0
##    probabilities: 0.327 0.265 0.327 0.082 0.000 
##   left son=3892 (16 obs) right son=3893 (33 obs)
##   Primary splits:
##       copd              < 0.5    to the right, improve=1.7300560, (0 missing)
##       reimbursement2008 < 5825   to the left,  improve=1.6040820, (0 missing)
##       age               < 67.5   to the right, improve=1.2805610, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.0381360, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8306573, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 25990  to the right, agree=0.755, adj=0.250, (0 split)
##       age               < 65.5   to the left,  agree=0.735, adj=0.188, (0 split)
##       bucket2008        < 3.5    to the right, agree=0.735, adj=0.188, (0 split)
## 
## Node number 1947: 63 observations,    complexity param=0.0005324004
##   predicted class=B2  expected loss=0.5873016  P(node) =0.00315
##     class counts:     8    26    22     7     0
##    probabilities: 0.127 0.413 0.349 0.111 0.000 
##   left son=3894 (33 obs) right son=3895 (30 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=2.2784990, (0 missing)
##       age               < 73.5   to the left,  improve=1.4389340, (0 missing)
##       reimbursement2008 < 14505  to the left,  improve=1.1107860, (0 missing)
##       copd              < 0.5    to the left,  improve=0.7714286, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6362229, (0 missing)
##   Surrogate splits:
##       alzheimers        < 0.5    to the left,  agree=0.651, adj=0.267, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.635, adj=0.233, (0 split)
##       reimbursement2008 < 13275  to the left,  agree=0.635, adj=0.233, (0 split)
##       copd              < 0.5    to the left,  agree=0.587, adj=0.133, (0 split)
##       stroke            < 0.5    to the left,  agree=0.587, adj=0.133, (0 split)
## 
## Node number 1968: 38 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5  P(node) =0.0019
##     class counts:    19    12     2     4     1
##    probabilities: 0.500 0.316 0.053 0.105 0.026 
##   left son=3936 (30 obs) right son=3937 (8 obs)
##   Primary splits:
##       age               < 67.5   to the right, improve=1.4745610, (0 missing)
##       reimbursement2008 < 14135  to the left,  improve=0.7888471, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5412281, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.5108359, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=0.3373819, (0 missing)
## 
## Node number 1969: 18 observations
##   predicted class=B2  expected loss=0.5555556  P(node) =0.0009
##     class counts:     2     8     4     2     2
##    probabilities: 0.111 0.444 0.222 0.111 0.111 
## 
## Node number 1970: 85 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5529412  P(node) =0.00425
##     class counts:    27    38    11     8     1
##    probabilities: 0.318 0.447 0.129 0.094 0.012 
##   left son=3940 (59 obs) right son=3941 (26 obs)
##   Primary splits:
##       age               < 80.5   to the left,  improve=1.2457550, (0 missing)
##       reimbursement2008 < 5820   to the left,  improve=1.0846660, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7174773, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5925134, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3022536, (0 missing)
## 
## Node number 1971: 42 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.452381  P(node) =0.0021
##     class counts:     4    23     6     9     0
##    probabilities: 0.095 0.548 0.143 0.214 0.000 
##   left son=3942 (32 obs) right son=3943 (10 obs)
##   Primary splits:
##       age               < 67.5   to the right, improve=2.2755950, (0 missing)
##       reimbursement2008 < 6595   to the right, improve=0.5809524, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.2880952, (0 missing)
##       copd              < 0.5    to the right, improve=0.2861722, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.1707875, (0 missing)
## 
## Node number 1972: 16 observations
##   predicted class=B1  expected loss=0.625  P(node) =0.0008
##     class counts:     6     6     4     0     0
##    probabilities: 0.375 0.375 0.250 0.000 0.000 
## 
## Node number 1973: 21 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5714286  P(node) =0.00105
##     class counts:     4     9     1     7     0
##    probabilities: 0.190 0.429 0.048 0.333 0.000 
##   left son=3946 (10 obs) right son=3947 (11 obs)
##   Primary splits:
##       age               < 87     to the right, improve=0.9454545, (0 missing)
##       copd              < 0.5    to the right, improve=0.9423077, (0 missing)
##       reimbursement2008 < 10955  to the right, improve=0.4545455, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.2307692, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.1923077, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4780   to the right, agree=0.667, adj=0.3, (0 split)
##       osteoporosis      < 0.5    to the right, agree=0.619, adj=0.2, (0 split)
##       cancer            < 0.5    to the right, agree=0.571, adj=0.1, (0 split)
##       copd              < 0.5    to the right, agree=0.571, adj=0.1, (0 split)
## 
## Node number 1974: 17 observations
##   predicted class=B2  expected loss=0.2352941  P(node) =0.00085
##     class counts:     1    13     2     1     0
##    probabilities: 0.059 0.765 0.118 0.059 0.000 
## 
## Node number 1975: 45 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4666667  P(node) =0.00225
##     class counts:     5    24    14     2     0
##    probabilities: 0.111 0.533 0.311 0.044 0.000 
##   left son=3950 (23 obs) right son=3951 (22 obs)
##   Primary splits:
##       reimbursement2008 < 5595   to the left,  improve=2.8877470, (0 missing)
##       age               < 70.5   to the left,  improve=0.7770751, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4450593, (0 missing)
##       copd              < 0.5    to the right, improve=0.2106952, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1447005, (0 missing)
##   Surrogate splits:
##       osteoporosis  < 0.5    to the right, agree=0.667, adj=0.318, (0 split)
##       age           < 70.5   to the left,  agree=0.622, adj=0.227, (0 split)
##       bucket2008    < 2.5    to the left,  agree=0.622, adj=0.227, (0 split)
##       copd          < 0.5    to the left,  agree=0.578, adj=0.136, (0 split)
##       heart.failure < 0.5    to the right, agree=0.578, adj=0.136, (0 split)
## 
## Node number 1978: 216 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5462963  P(node) =0.0108
##     class counts:    42    98    56    18     2
##    probabilities: 0.194 0.454 0.259 0.083 0.009 
##   left son=3956 (52 obs) right son=3957 (164 obs)
##   Primary splits:
##       reimbursement2008 < 15105  to the right, improve=1.4684180, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.4512310, (0 missing)
##       age               < 71.5   to the right, improve=1.0436270, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8503280, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7569892, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.926, adj=0.692, (0 split)
##       age        < 55.5   to the left,  agree=0.764, adj=0.019, (0 split)
## 
## Node number 1979: 9 observations
##   predicted class=B3  expected loss=0.5555556  P(node) =0.00045
##     class counts:     1     1     4     3     0
##    probabilities: 0.111 0.111 0.444 0.333 0.000 
## 
## Node number 1984: 43 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5813953  P(node) =0.00215
##     class counts:    18     9    12     2     2
##    probabilities: 0.419 0.209 0.279 0.047 0.047 
##   left son=3968 (11 obs) right son=3969 (32 obs)
##   Primary splits:
##       reimbursement2008 < 8495   to the left,  improve=2.1203750, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.3253000, (0 missing)
##       age               < 96.5   to the left,  improve=1.2164460, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9252995, (0 missing)
##       copd              < 0.5    to the right, improve=0.5070379, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.884, adj=0.545, (0 split)
## 
## Node number 1985: 24 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.625  P(node) =0.0012
##     class counts:     4     9     9     2     0
##    probabilities: 0.167 0.375 0.375 0.083 0.000 
##   left son=3970 (8 obs) right son=3971 (16 obs)
##   Primary splits:
##       reimbursement2008 < 9045   to the left,  improve=2.2916670, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8921911, (0 missing)
##       age               < 87.5   to the left,  improve=0.7722222, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.7722222, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.4166667, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.750, adj=0.250, (0 split)
##       age        < 89.5   to the right, agree=0.708, adj=0.125, (0 split)
## 
## Node number 1986: 11 observations
##   predicted class=B1  expected loss=0.4545455  P(node) =0.00055
##     class counts:     6     1     1     3     0
##    probabilities: 0.545 0.091 0.091 0.273 0.000 
## 
## Node number 1987: 268 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6231343  P(node) =0.0134
##     class counts:    60   101    49    50     8
##    probabilities: 0.224 0.377 0.183 0.187 0.030 
##   left son=3974 (177 obs) right son=3975 (91 obs)
##   Primary splits:
##       age               < 77.5   to the left,  improve=1.6839510, (0 missing)
##       reimbursement2008 < 14425  to the left,  improve=1.3251930, (0 missing)
##       stroke            < 0.5    to the right, improve=1.2532710, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.9809812, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9444366, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 13575  to the left,  agree=0.679, adj=0.055, (0 split)
## 
## Node number 1990: 235 observations,    complexity param=0.0003650745
##   predicted class=B2  expected loss=0.6042553  P(node) =0.01175
##     class counts:    45    93    59    32     6
##    probabilities: 0.191 0.396 0.251 0.136 0.026 
##   left son=3980 (210 obs) right son=3981 (25 obs)
##   Primary splits:
##       reimbursement2008 < 6170   to the left,  improve=2.3734140, (0 missing)
##       age               < 81.5   to the right, improve=1.4517590, (0 missing)
##       depression        < 0.5    to the right, improve=0.7995092, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.6947270, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6162007, (0 missing)
## 
## Node number 1991: 12 observations
##   predicted class=B3  expected loss=0.3333333  P(node) =0.0006
##     class counts:     2     2     8     0     0
##    probabilities: 0.167 0.167 0.667 0.000 0.000 
## 
## Node number 2004: 88 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.4318182  P(node) =0.0044
##     class counts:    16    50    14     7     1
##    probabilities: 0.182 0.568 0.159 0.080 0.011 
##   left son=4008 (19 obs) right son=4009 (69 obs)
##   Primary splits:
##       reimbursement2008 < 3725   to the left,  improve=1.1251130, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.9988702, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.7978634, (0 missing)
##       age               < 90.5   to the left,  improve=0.6812354, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.5300418, (0 missing)
## 
## Node number 2005: 19 observations
##   predicted class=B2  expected loss=0.2105263  P(node) =0.00095
##     class counts:     0    15     1     3     0
##    probabilities: 0.000 0.789 0.053 0.158 0.000 
## 
## Node number 2006: 16 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0008
##     class counts:     3     8     3     2     0
##    probabilities: 0.188 0.500 0.188 0.125 0.000 
## 
## Node number 2007: 9 observations
##   predicted class=B3  expected loss=0.5555556  P(node) =0.00045
##     class counts:     1     2     4     2     0
##    probabilities: 0.111 0.222 0.444 0.222 0.000 
## 
## Node number 2012: 35 observations,    complexity param=0.0002028192
##   predicted class=B3  expected loss=0.6571429  P(node) =0.00175
##     class counts:     7    11    12     5     0
##    probabilities: 0.200 0.314 0.343 0.143 0.000 
##   left son=4024 (13 obs) right son=4025 (22 obs)
##   Primary splits:
##       age               < 72.5   to the left,  improve=1.2093910, (0 missing)
##       reimbursement2008 < 6400   to the right, improve=0.9571429, (0 missing)
##       depression        < 0.5    to the right, improve=0.4095238, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.3340226, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1910973, (0 missing)
##   Surrogate splits:
##       stroke < 0.5    to the right, agree=0.657, adj=0.077, (0 split)
## 
## Node number 2013: 218 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5229358  P(node) =0.0109
##     class counts:    22   104    57    30     5
##    probabilities: 0.101 0.477 0.261 0.138 0.023 
##   left son=4026 (187 obs) right son=4027 (31 obs)
##   Primary splits:
##       reimbursement2008 < 7265   to the right, improve=1.4088950, (0 missing)
##       copd              < 0.5    to the left,  improve=1.3174740, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.2029980, (0 missing)
##       age               < 75.5   to the left,  improve=0.7552085, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.5102534, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.913, adj=0.387, (0 split)
## 
## Node number 2014: 22 observations
##   predicted class=B2  expected loss=0.2272727  P(node) =0.0011
##     class counts:     0    17     4     0     1
##    probabilities: 0.000 0.773 0.182 0.000 0.045 
## 
## Node number 2015: 10 observations
##   predicted class=B3  expected loss=0.6  P(node) =0.0005
##     class counts:     0     3     4     3     0
##    probabilities: 0.000 0.300 0.400 0.300 0.000 
## 
## Node number 2032: 67 observations,    complexity param=0.0004563432
##   predicted class=B1  expected loss=0.6716418  P(node) =0.00335
##     class counts:    22    12    17    16     0
##    probabilities: 0.328 0.179 0.254 0.239 0.000 
##   left son=4064 (59 obs) right son=4065 (8 obs)
##   Primary splits:
##       reimbursement2008 < 18390  to the right, improve=1.7171140, (0 missing)
##       stroke            < 0.5    to the right, improve=1.6606280, (0 missing)
##       cancer            < 0.5    to the right, improve=1.0990060, (0 missing)
##       age               < 80.5   to the left,  improve=0.9955676, (0 missing)
##       bucket2008        < 3.5    to the right, improve=0.8525373, (0 missing)
## 
## Node number 2033: 28 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.6071429  P(node) =0.0014
##     class counts:     5    11     3     9     0
##    probabilities: 0.179 0.393 0.107 0.321 0.000 
##   left son=4066 (9 obs) right son=4067 (19 obs)
##   Primary splits:
##       reimbursement2008 < 16540  to the left,  improve=2.1796160, (0 missing)
##       depression        < 0.5    to the left,  improve=1.2857140, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.9047619, (0 missing)
##       age               < 70.5   to the left,  improve=0.8158730, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3630952, (0 missing)
## 
## Node number 2034: 41 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5121951  P(node) =0.00205
##     class counts:     7    20     6     4     4
##    probabilities: 0.171 0.488 0.146 0.098 0.098 
##   left son=4068 (32 obs) right son=4069 (9 obs)
##   Primary splits:
##       age               < 83.5   to the left,  improve=2.1888550, (0 missing)
##       reimbursement2008 < 25405  to the right, improve=1.4735770, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9644375, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.8832995, (0 missing)
##       stroke            < 0.5    to the right, improve=0.7966955, (0 missing)
## 
## Node number 2035: 97 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6907216  P(node) =0.00485
##     class counts:    14    30    23    26     4
##    probabilities: 0.144 0.309 0.237 0.268 0.041 
##   left son=4070 (81 obs) right son=4071 (16 obs)
##   Primary splits:
##       reimbursement2008 < 21150  to the left,  improve=2.1982790, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.8385610, (0 missing)
##       age               < 58     to the right, improve=1.5250180, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.8794627, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7745519, (0 missing)
## 
## Node number 2036: 125 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.568  P(node) =0.00625
##     class counts:    17    54    32    16     6
##    probabilities: 0.136 0.432 0.256 0.128 0.048 
##   left son=4072 (36 obs) right son=4073 (89 obs)
##   Primary splits:
##       reimbursement2008 < 22510  to the right, improve=1.5030360, (0 missing)
##       age               < 71.5   to the left,  improve=1.4083000, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.0672150, (0 missing)
##       bucket2008        < 3.5    to the right, improve=1.0234450, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9386667, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.72, adj=0.028, (0 split)
## 
## Node number 2037: 15 observations
##   predicted class=B3  expected loss=0.6  P(node) =0.00075
##     class counts:     0     3     6     4     2
##    probabilities: 0.000 0.200 0.400 0.267 0.133 
## 
## Node number 2038: 13 observations
##   predicted class=B2  expected loss=0.6153846  P(node) =0.00065
##     class counts:     1     5     3     3     1
##    probabilities: 0.077 0.385 0.231 0.231 0.077 
## 
## Node number 2039: 10 observations
##   predicted class=B3  expected loss=0.1  P(node) =0.0005
##     class counts:     0     0     9     1     0
##    probabilities: 0.000 0.000 0.900 0.100 0.000 
## 
## Node number 2044: 47 observations,    complexity param=0.0002662002
##   predicted class=B2  expected loss=0.4680851  P(node) =0.00235
##     class counts:     3    25    10     6     3
##    probabilities: 0.064 0.532 0.213 0.128 0.064 
##   left son=4088 (30 obs) right son=4089 (17 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=3.2804340, (0 missing)
##       age               < 81.5   to the left,  improve=1.9668850, (0 missing)
##       reimbursement2008 < 31080  to the right, improve=1.4612460, (0 missing)
##       copd              < 0.5    to the right, improve=1.1322990, (0 missing)
##       depression        < 0.5    to the right, improve=0.8569045, (0 missing)
##   Surrogate splits:
##       age               < 85.5   to the left,  agree=0.702, adj=0.176, (0 split)
##       reimbursement2008 < 31580  to the left,  agree=0.660, adj=0.059, (0 split)
## 
## Node number 2045: 44 observations,    complexity param=0.0002662002
##   predicted class=B2  expected loss=0.5681818  P(node) =0.0022
##     class counts:     3    19     7    15     0
##    probabilities: 0.068 0.432 0.159 0.341 0.000 
##   left son=4090 (11 obs) right son=4091 (33 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=1.5454550, (0 missing)
##       age               < 55.5   to the left,  improve=1.5257990, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.3346510, (0 missing)
##       reimbursement2008 < 29895  to the right, improve=0.8874459, (0 missing)
##       stroke            < 0.5    to the right, improve=0.7160173, (0 missing)
##   Surrogate splits:
##       age < 55.5   to the left,  agree=0.773, adj=0.091, (0 split)
## 
## Node number 2046: 97 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5979381  P(node) =0.00485
##     class counts:     6    39    17    28     7
##    probabilities: 0.062 0.402 0.175 0.289 0.072 
##   left son=4092 (26 obs) right son=4093 (71 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=1.5049540, (0 missing)
##       reimbursement2008 < 37785  to the left,  improve=1.3125260, (0 missing)
##       age               < 79.5   to the left,  improve=1.1547350, (0 missing)
##       cancer            < 0.5    to the right, improve=1.1520240, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9743395, (0 missing)
##   Surrogate splits:
##       heart.failure < 0.5    to the left,  agree=0.753, adj=0.077, (0 split)
## 
## Node number 2047: 234 observations,    complexity param=0.000507048
##   predicted class=B4  expected loss=0.6709402  P(node) =0.0117
##     class counts:    18    65    63    77    11
##    probabilities: 0.077 0.278 0.269 0.329 0.047 
##   left son=4094 (180 obs) right son=4095 (54 obs)
##   Primary splits:
##       reimbursement2008 < 37290  to the right, improve=2.5176640, (0 missing)
##       bucket2008        < 4.5    to the right, improve=2.4693040, (0 missing)
##       age               < 36.5   to the left,  improve=0.9682593, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8197802, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.8182531, (0 missing)
## 
## Node number 2570: 277 observations
##   predicted class=B1  expected loss=0.1371841  P(node) =0.01385
##     class counts:   239    21    10     7     0
##    probabilities: 0.863 0.076 0.036 0.025 0.000 
## 
## Node number 2571: 430 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1837209  P(node) =0.0215
##     class counts:   351    47    26     4     2
##    probabilities: 0.816 0.109 0.060 0.009 0.005 
##   left son=5142 (398 obs) right son=5143 (32 obs)
##   Primary splits:
##       reimbursement2008 < 475    to the left,  improve=1.1570540, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.5902656, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4826179, (0 missing)
##       age               < 86.5   to the left,  improve=0.4570367, (0 missing)
##       kidney            < 0.5    to the right, improve=0.2437930, (0 missing)
## 
## Node number 2842: 60 observations
##   predicted class=B1  expected loss=0.2666667  P(node) =0.003
##     class counts:    44    12     3     1     0
##    probabilities: 0.733 0.200 0.050 0.017 0.000 
## 
## Node number 2843: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     3     4     0     0     0
##    probabilities: 0.429 0.571 0.000 0.000 0.000 
## 
## Node number 2882: 197 observations
##   predicted class=B1  expected loss=0.1928934  P(node) =0.00985
##     class counts:   159    18    13     7     0
##    probabilities: 0.807 0.091 0.066 0.036 0.000 
## 
## Node number 2883: 59 observations,    complexity param=5.07048e-05
##   predicted class=B1  expected loss=0.3389831  P(node) =0.00295
##     class counts:    39    10     8     2     0
##    probabilities: 0.661 0.169 0.136 0.034 0.000 
##   left son=5766 (51 obs) right son=5767 (8 obs)
##   Primary splits:
##       reimbursement2008 < 1115   to the right, improve=1.7797440, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.2458970, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9810446, (0 missing)
##       age               < 83.5   to the left,  improve=0.7705825, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.4388154, (0 missing)
## 
## Node number 2884: 109 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.2844037  P(node) =0.00545
##     class counts:    78    21     9     1     0
##    probabilities: 0.716 0.193 0.083 0.009 0.000 
##   left son=5768 (79 obs) right son=5769 (30 obs)
##   Primary splits:
##       age               < 77.5   to the right, improve=1.7532540, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.7212762, (0 missing)
##       reimbursement2008 < 1545   to the left,  improve=0.6234163, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.4323641, (0 missing)
##       kidney            < 0.5    to the right, improve=0.4275433, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1345   to the right, agree=0.752, adj=0.1, (0 split)
## 
## Node number 2885: 49 observations
##   predicted class=B1  expected loss=0.244898  P(node) =0.00245
##     class counts:    37     4     4     4     0
##    probabilities: 0.755 0.082 0.082 0.082 0.000 
## 
## Node number 2892: 32 observations
##   predicted class=B1  expected loss=0.1875  P(node) =0.0016
##     class counts:    26     4     1     1     0
##    probabilities: 0.813 0.125 0.031 0.031 0.000 
## 
## Node number 2893: 20 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.45  P(node) =0.001
##     class counts:    11     6     1     2     0
##    probabilities: 0.550 0.300 0.050 0.100 0.000 
##   left son=5786 (9 obs) right son=5787 (11 obs)
##   Primary splits:
##       reimbursement2008 < 1115   to the left,  improve=1.4757580, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.1500000, (0 missing)
##       age               < 54     to the right, improve=0.5666667, (0 missing)
##   Surrogate splits:
##       diabetes      < 0.5    to the left,  agree=0.75, adj=0.444, (0 split)
##       age           < 41     to the left,  agree=0.70, adj=0.333, (0 split)
##       depression    < 0.5    to the right, agree=0.60, adj=0.111, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.60, adj=0.111, (0 split)
## 
## Node number 2894: 15 observations
##   predicted class=B1  expected loss=0.2666667  P(node) =0.00075
##     class counts:    11     3     1     0     0
##    probabilities: 0.733 0.200 0.067 0.000 0.000 
## 
## Node number 2895: 20 observations,    complexity param=8.450799e-05
##   predicted class=B2  expected loss=0.45  P(node) =0.001
##     class counts:     9    11     0     0     0
##    probabilities: 0.450 0.550 0.000 0.000 0.000 
##   left son=5790 (11 obs) right son=5791 (9 obs)
##   Primary splits:
##       reimbursement2008 < 1275   to the right, improve=0.445454500, (0 missing)
##       age               < 64.5   to the left,  improve=0.100000000, (0 missing)
##       depression        < 0.5    to the left,  improve=0.001010101, (0 missing)
##   Surrogate splits:
##       age        < 46     to the right, agree=0.6, adj=0.111, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.6, adj=0.111, (0 split)
##       depression < 0.5    to the right, agree=0.6, adj=0.111, (0 split)
## 
## Node number 2948: 8 observations
##   predicted class=B1  expected loss=0  P(node) =0.0004
##     class counts:     8     0     0     0     0
##    probabilities: 1.000 0.000 0.000 0.000 0.000 
## 
## Node number 2949: 137 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.2992701  P(node) =0.00685
##     class counts:    96    25    13     3     0
##    probabilities: 0.701 0.182 0.095 0.022 0.000 
##   left son=5898 (10 obs) right son=5899 (127 obs)
##   Primary splits:
##       copd              < 0.5    to the right, improve=0.7930226, (0 missing)
##       reimbursement2008 < 875    to the left,  improve=0.5527217, (0 missing)
##       age               < 79.5   to the left,  improve=0.4583429, (0 missing)
##       depression        < 0.5    to the right, improve=0.4287322, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1222173, (0 missing)
## 
## Node number 2950: 8 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.0004
##     class counts:     6     1     0     1     0
##    probabilities: 0.750 0.125 0.000 0.125 0.000 
## 
## Node number 2951: 20 observations,    complexity param=6.519188e-05
##   predicted class=B2  expected loss=0.6  P(node) =0.001
##     class counts:     7     8     4     1     0
##    probabilities: 0.350 0.400 0.200 0.050 0.000 
##   left son=5902 (7 obs) right son=5903 (13 obs)
##   Primary splits:
##       age               < 66.5   to the left,  improve=0.3131868, (0 missing)
##       reimbursement2008 < 770    to the left,  improve=0.3131868, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 805    to the right, agree=0.85, adj=0.571, (0 split)
## 
## Node number 3026: 14 observations
##   predicted class=B1  expected loss=0.07142857  P(node) =0.0007
##     class counts:    13     1     0     0     0
##    probabilities: 0.929 0.071 0.000 0.000 0.000 
## 
## Node number 3027: 125 observations,    complexity param=6.084576e-05
##   predicted class=B1  expected loss=0.344  P(node) =0.00625
##     class counts:    82    30    12     0     1
##    probabilities: 0.656 0.240 0.096 0.000 0.008 
##   left son=6054 (10 obs) right son=6055 (115 obs)
##   Primary splits:
##       arthritis         < 0.5    to the right, improve=0.9610435, (0 missing)
##       kidney            < 0.5    to the right, improve=0.8457324, (0 missing)
##       age               < 73.5   to the right, improve=0.7907549, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6473119, (0 missing)
##       reimbursement2008 < 925    to the right, improve=0.5392281, (0 missing)
## 
## Node number 3028: 9 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.00045
##     class counts:     4     5     0     0     0
##    probabilities: 0.444 0.556 0.000 0.000 0.000 
## 
## Node number 3029: 59 observations
##   predicted class=B1  expected loss=0.3050847  P(node) =0.00295
##     class counts:    41     8     5     5     0
##    probabilities: 0.695 0.136 0.085 0.085 0.000 
## 
## Node number 3030: 20 observations
##   predicted class=B1  expected loss=0.45  P(node) =0.001
##     class counts:    11     7     1     1     0
##    probabilities: 0.550 0.350 0.050 0.050 0.000 
## 
## Node number 3031: 9 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.00045
##     class counts:     3     5     1     0     0
##    probabilities: 0.333 0.556 0.111 0.000 0.000 
## 
## Node number 3046: 31 observations
##   predicted class=B1  expected loss=0.4516129  P(node) =0.00155
##     class counts:    17     5     7     2     0
##    probabilities: 0.548 0.161 0.226 0.065 0.000 
## 
## Node number 3047: 25 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.48  P(node) =0.00125
##     class counts:     8    13     4     0     0
##    probabilities: 0.320 0.520 0.160 0.000 0.000 
##   left son=6094 (18 obs) right son=6095 (7 obs)
##   Primary splits:
##       reimbursement2008 < 1435   to the left,  improve=2.7225400, (0 missing)
##       age               < 74.5   to the left,  improve=0.3782353, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.3316667, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.2463492, (0 missing)
##   Surrogate splits:
##       age < 75.5   to the left,  agree=0.76, adj=0.143, (0 split)
## 
## Node number 3072: 40 observations
##   predicted class=B1  expected loss=0.175  P(node) =0.002
##     class counts:    33     3     4     0     0
##    probabilities: 0.825 0.075 0.100 0.000 0.000 
## 
## Node number 3073: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     3     0     4     0     0
##    probabilities: 0.429 0.000 0.571 0.000 0.000 
## 
## Node number 3076: 23 observations
##   predicted class=B1  expected loss=0.2173913  P(node) =0.00115
##     class counts:    18     3     1     1     0
##    probabilities: 0.783 0.130 0.043 0.043 0.000 
## 
## Node number 3077: 69 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3768116  P(node) =0.00345
##     class counts:    43    19     6     0     1
##    probabilities: 0.623 0.275 0.087 0.000 0.014 
##   left son=6154 (59 obs) right son=6155 (10 obs)
##   Primary splits:
##       reimbursement2008 < 2295   to the left,  improve=0.9161385, (0 missing)
##       age               < 47     to the right, improve=0.6125604, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.4294916, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2435600, (0 missing)
## 
## Node number 3084: 58 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.4137931  P(node) =0.0029
##     class counts:    34    20     4     0     0
##    probabilities: 0.586 0.345 0.069 0.000 0.000 
##   left son=6168 (49 obs) right son=6169 (9 obs)
##   Primary splits:
##       reimbursement2008 < 2415   to the left,  improve=0.73782160, (0 missing)
##       age               < 77.5   to the right, improve=0.37655170, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.12048330, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.03843207, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.01005232, (0 missing)
##   Surrogate splits:
##       copd < 0.5    to the left,  agree=0.879, adj=0.222, (0 split)
## 
## Node number 3085: 14 observations
##   predicted class=B1  expected loss=0.3571429  P(node) =0.0007
##     class counts:     9     1     2     2     0
##    probabilities: 0.643 0.071 0.143 0.143 0.000 
## 
## Node number 3086: 7 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.00035
##     class counts:     5     1     0     1     0
##    probabilities: 0.714 0.143 0.000 0.143 0.000 
## 
## Node number 3087: 21 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.7142857  P(node) =0.00105
##     class counts:     6     6     5     4     0
##    probabilities: 0.286 0.286 0.238 0.190 0.000 
##   left son=6174 (13 obs) right son=6175 (8 obs)
##   Primary splits:
##       reimbursement2008 < 2170   to the left,  improve=0.7921245, (0 missing)
##       age               < 84.5   to the right, improve=0.6190476, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3412698, (0 missing)
##   Surrogate splits:
##       age        < 82.5   to the right, agree=0.762, adj=0.375, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.667, adj=0.125, (0 split)
## 
## Node number 3112: 30 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0015
##     class counts:    20    10     0     0     0
##    probabilities: 0.667 0.333 0.000 0.000 0.000 
##   left son=6224 (23 obs) right son=6225 (7 obs)
##   Primary splits:
##       age               < 77.5   to the left,  improve=2.6501040, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.1111110, (0 missing)
##       reimbursement2008 < 2885   to the left,  improve=0.6625259, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.0297619, (0 missing)
## 
## Node number 3113: 11 observations
##   predicted class=B2  expected loss=0.3636364  P(node) =0.00055
##     class counts:     4     7     0     0     0
##    probabilities: 0.364 0.636 0.000 0.000 0.000 
## 
## Node number 3114: 18 observations
##   predicted class=B1  expected loss=0.2777778  P(node) =0.0009
##     class counts:    13     2     3     0     0
##    probabilities: 0.722 0.111 0.167 0.000 0.000 
## 
## Node number 3115: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     2     4     0     0     1
##    probabilities: 0.286 0.571 0.000 0.000 0.143 
## 
## Node number 3162: 17 observations
##   predicted class=B1  expected loss=0.4705882  P(node) =0.00085
##     class counts:     9     5     1     2     0
##    probabilities: 0.529 0.294 0.059 0.118 0.000 
## 
## Node number 3163: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     1     4     0     2     0
##    probabilities: 0.143 0.571 0.000 0.286 0.000 
## 
## Node number 3180: 8 observations
##   predicted class=B1  expected loss=0.125  P(node) =0.0004
##     class counts:     7     0     0     1     0
##    probabilities: 0.875 0.000 0.000 0.125 0.000 
## 
## Node number 3181: 105 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5809524  P(node) =0.00525
##     class counts:    44    37    21     2     1
##    probabilities: 0.419 0.352 0.200 0.019 0.010 
##   left son=6362 (45 obs) right son=6363 (60 obs)
##   Primary splits:
##       age               < 75.5   to the right, improve=1.0650790, (0 missing)
##       reimbursement2008 < 2955   to the left,  improve=0.9904762, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7462449, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.7161905, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6605234, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1930   to the left,  agree=0.610, adj=0.089, (0 split)
##       arthritis         < 0.5    to the right, agree=0.581, adj=0.022, (0 split)
## 
## Node number 3332: 70 observations
##   predicted class=B1  expected loss=0.3  P(node) =0.0035
##     class counts:    49    12     5     3     1
##    probabilities: 0.700 0.171 0.071 0.043 0.014 
## 
## Node number 3333: 16 observations
##   predicted class=B2  expected loss=0.5625  P(node) =0.0008
##     class counts:     6     7     2     1     0
##    probabilities: 0.375 0.438 0.125 0.062 0.000 
## 
## Node number 3334: 8 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.0004
##     class counts:     6     1     1     0     0
##    probabilities: 0.750 0.125 0.125 0.000 0.000 
## 
## Node number 3335: 50 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.54  P(node) =0.0025
##     class counts:    23    23     2     2     0
##    probabilities: 0.460 0.460 0.040 0.040 0.000 
##   left son=6670 (42 obs) right son=6671 (8 obs)
##   Primary splits:
##       age               < 89.5   to the left,  improve=0.7633333, (0 missing)
##       reimbursement2008 < 2305   to the left,  improve=0.5728571, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.4736508, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3203509, (0 missing)
##       kidney            < 0.5    to the right, improve=0.1300000, (0 missing)
## 
## Node number 3340: 33 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.4242424  P(node) =0.00165
##     class counts:    19    10     3     0     1
##    probabilities: 0.576 0.303 0.091 0.000 0.030 
##   left son=6680 (19 obs) right son=6681 (14 obs)
##   Primary splits:
##       age               < 77.5   to the right, improve=2.15584400, (0 missing)
##       reimbursement2008 < 1845   to the right, improve=0.38814230, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.37012990, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.22177820, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.03282828, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1690   to the right, agree=0.636, adj=0.143, (0 split)
## 
## Node number 3341: 30 observations,    complexity param=0.000190143
##   predicted class=B2  expected loss=0.4333333  P(node) =0.0015
##     class counts:    12    17     1     0     0
##    probabilities: 0.400 0.567 0.033 0.000 0.000 
##   left son=6682 (12 obs) right son=6683 (18 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=1.1444440, (0 missing)
##       reimbursement2008 < 2375   to the right, improve=0.9651515, (0 missing)
##       age               < 83     to the left,  improve=0.7188537, (0 missing)
##       kidney            < 0.5    to the right, improve=0.6015152, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.1469697, (0 missing)
## 
## Node number 3342: 10 observations
##   predicted class=B1  expected loss=0.2  P(node) =0.0005
##     class counts:     8     0     1     1     0
##    probabilities: 0.800 0.000 0.100 0.100 0.000 
## 
## Node number 3343: 15 observations
##   predicted class=B2  expected loss=0.6  P(node) =0.00075
##     class counts:     4     6     1     4     0
##    probabilities: 0.267 0.400 0.067 0.267 0.000 
## 
## Node number 3344: 211 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.3791469  P(node) =0.01055
##     class counts:   131    51    18    10     1
##    probabilities: 0.621 0.242 0.085 0.047 0.005 
##   left son=6688 (96 obs) right son=6689 (115 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=1.4607100, (0 missing)
##       reimbursement2008 < 1735   to the left,  improve=1.3331950, (0 missing)
##       age               < 70.5   to the left,  improve=1.0529550, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.7906734, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3086469, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2375   to the right, agree=0.564, adj=0.042, (0 split)
##       age               < 69.5   to the left,  agree=0.559, adj=0.031, (0 split)
##       cancer            < 0.5    to the right, agree=0.559, adj=0.031, (0 split)
## 
## Node number 3345: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     2     5     0     0     0
##    probabilities: 0.286 0.714 0.000 0.000 0.000 
## 
## Node number 3348: 18 observations
##   predicted class=B1  expected loss=0.5555556  P(node) =0.0009
##     class counts:     8     5     2     3     0
##    probabilities: 0.444 0.278 0.111 0.167 0.000 
## 
## Node number 3349: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     1     5     1     1     0
##    probabilities: 0.125 0.625 0.125 0.125 0.000 
## 
## Node number 3352: 98 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5714286  P(node) =0.0049
##     class counts:    41    42     6     8     1
##    probabilities: 0.418 0.429 0.061 0.082 0.010 
##   left son=6704 (88 obs) right son=6705 (10 obs)
##   Primary splits:
##       reimbursement2008 < 2165   to the left,  improve=1.2299630, (0 missing)
##       age               < 72.5   to the left,  improve=0.8171297, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.7814001, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5288983, (0 missing)
##       cancer            < 0.5    to the right, improve=0.4885488, (0 missing)
## 
## Node number 3353: 17 observations
##   predicted class=B1  expected loss=0.5882353  P(node) =0.00085
##     class counts:     7     4     5     0     1
##    probabilities: 0.412 0.235 0.294 0.000 0.059 
## 
## Node number 3354: 23 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.6086957  P(node) =0.00115
##     class counts:     8     9     6     0     0
##    probabilities: 0.348 0.391 0.261 0.000 0.000 
##   left son=6708 (16 obs) right son=6709 (7 obs)
##   Primary splits:
##       reimbursement2008 < 2305   to the right, improve=0.9697205, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.3880105, (0 missing)
##       age               < 70.5   to the right, improve=0.3150502, (0 missing)
## 
## Node number 3355: 8 observations
##   predicted class=B2  expected loss=0.25  P(node) =0.0004
##     class counts:     0     6     2     0     0
##    probabilities: 0.000 0.750 0.250 0.000 0.000 
## 
## Node number 3358: 8 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0004
##     class counts:     4     1     1     2     0
##    probabilities: 0.500 0.125 0.125 0.250 0.000 
## 
## Node number 3359: 17 observations
##   predicted class=B3  expected loss=0.5294118  P(node) =0.00085
##     class counts:     5     2     8     1     1
##    probabilities: 0.294 0.118 0.471 0.059 0.059 
## 
## Node number 3424: 28 observations
##   predicted class=B1  expected loss=0.2142857  P(node) =0.0014
##     class counts:    22     1     2     2     1
##    probabilities: 0.786 0.036 0.071 0.071 0.036 
## 
## Node number 3425: 34 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.4117647  P(node) =0.0017
##     class counts:    20    10     2     2     0
##    probabilities: 0.588 0.294 0.059 0.059 0.000 
##   left son=6850 (10 obs) right son=6851 (24 obs)
##   Primary splits:
##       reimbursement2008 < 1865   to the right, improve=1.9088240, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.1388240, (0 missing)
##       age               < 65.5   to the right, improve=1.0445380, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.4073084, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3640867, (0 missing)
##   Surrogate splits:
##       age < 37.5   to the left,  agree=0.765, adj=0.2, (0 split)
## 
## Node number 3428: 25 observations
##   predicted class=B1  expected loss=0.44  P(node) =0.00125
##     class counts:    14     7     3     1     0
##    probabilities: 0.560 0.280 0.120 0.040 0.000 
## 
## Node number 3429: 29 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6551724  P(node) =0.00145
##     class counts:     7    10     9     3     0
##    probabilities: 0.241 0.345 0.310 0.103 0.000 
##   left son=6858 (22 obs) right son=6859 (7 obs)
##   Primary splits:
##       age               < 55     to the right, improve=1.5638150, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.2323050, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.9144648, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.6007260, (0 missing)
##       reimbursement2008 < 2075   to the right, improve=0.5667015, (0 missing)
##   Surrogate splits:
##       kidney < 0.5    to the left,  agree=0.793, adj=0.143, (0 split)
## 
## Node number 3434: 10 observations
##   predicted class=B2  expected loss=0.2  P(node) =0.0005
##     class counts:     2     8     0     0     0
##    probabilities: 0.200 0.800 0.000 0.000 0.000 
## 
## Node number 3435: 99 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.4949495  P(node) =0.00495
##     class counts:    32    50    16     1     0
##    probabilities: 0.323 0.505 0.162 0.010 0.000 
##   left son=6870 (46 obs) right son=6871 (53 obs)
##   Primary splits:
##       reimbursement2008 < 2045   to the right, improve=1.4422070, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.6616256, (0 missing)
##       age               < 75.5   to the right, improve=0.5566090, (0 missing)
##       copd              < 0.5    to the right, improve=0.5057552, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.4451178, (0 missing)
##   Surrogate splits:
##       age          < 72.5   to the left,  agree=0.576, adj=0.087, (0 split)
##       diabetes     < 0.5    to the right, agree=0.566, adj=0.065, (0 split)
##       arthritis    < 0.5    to the right, agree=0.556, adj=0.043, (0 split)
##       kidney       < 0.5    to the right, agree=0.556, adj=0.043, (0 split)
##       osteoporosis < 0.5    to the right, agree=0.556, adj=0.043, (0 split)
## 
## Node number 3466: 14 observations
##   predicted class=B1  expected loss=0.2142857  P(node) =0.0007
##     class counts:    11     2     0     1     0
##    probabilities: 0.786 0.143 0.000 0.071 0.000 
## 
## Node number 3467: 55 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5090909  P(node) =0.00275
##     class counts:    27    17     8     3     0
##    probabilities: 0.491 0.309 0.145 0.055 0.000 
##   left son=6934 (41 obs) right son=6935 (14 obs)
##   Primary splits:
##       age               < 83.5   to the left,  improve=2.7071900, (0 missing)
##       reimbursement2008 < 2680   to the right, improve=1.7662000, (0 missing)
##       copd              < 0.5    to the left,  improve=1.5148270, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.3909091, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1531834, (0 missing)
## 
## Node number 3468: 58 observations,    complexity param=0.0001014096
##   predicted class=B1  expected loss=0.4310345  P(node) =0.0029
##     class counts:    33    11    10     2     2
##    probabilities: 0.569 0.190 0.172 0.034 0.034 
##   left son=6936 (7 obs) right son=6937 (51 obs)
##   Primary splits:
##       reimbursement2008 < 3325   to the right, improve=2.0209600, (0 missing)
##       age               < 70.5   to the right, improve=0.7361795, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.5862069, (0 missing)
##       kidney            < 0.5    to the right, improve=0.3220159, (0 missing)
##       copd              < 0.5    to the left,  improve=0.2258621, (0 missing)
## 
## Node number 3469: 46 observations,    complexity param=0.0002662002
##   predicted class=B2  expected loss=0.6086957  P(node) =0.0023
##     class counts:    17    18     9     2     0
##    probabilities: 0.370 0.391 0.196 0.043 0.000 
##   left son=6938 (33 obs) right son=6939 (13 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=1.2037090, (0 missing)
##       age               < 81.5   to the right, improve=0.9942551, (0 missing)
##       reimbursement2008 < 2695   to the left,  improve=0.9260870, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7830762, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4167302, (0 missing)
##   Surrogate splits:
##       copd              < 0.5    to the left,  agree=0.783, adj=0.231, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.739, adj=0.077, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.739, adj=0.077, (0 split)
##       reimbursement2008 < 3385   to the left,  agree=0.739, adj=0.077, (0 split)
## 
## Node number 3490: 67 observations,    complexity param=0.000253524
##   predicted class=B1  expected loss=0.4626866  P(node) =0.00335
##     class counts:    36    18     6     7     0
##    probabilities: 0.537 0.269 0.090 0.104 0.000 
##   left son=6980 (23 obs) right son=6981 (44 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=1.7004600, (0 missing)
##       reimbursement2008 < 2850   to the right, improve=0.8931479, (0 missing)
##       age               < 87.5   to the right, improve=0.8361371, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5107368, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4996072, (0 missing)
##   Surrogate splits:
##       age    < 41.5   to the left,  agree=0.687, adj=0.087, (0 split)
##       stroke < 0.5    to the right, agree=0.672, adj=0.043, (0 split)
## 
## Node number 3491: 58 observations,    complexity param=0.0006084576
##   predicted class=B2  expected loss=0.5  P(node) =0.0029
##     class counts:    20    29     5     4     0
##    probabilities: 0.345 0.500 0.086 0.069 0.000 
##   left son=6982 (13 obs) right son=6983 (45 obs)
##   Primary splits:
##       age               < 67.5   to the left,  improve=1.9273210, (0 missing)
##       reimbursement2008 < 3285   to the right, improve=1.2543850, (0 missing)
##       depression        < 0.5    to the left,  improve=1.0681200, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6646677, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.3607892, (0 missing)
## 
## Node number 3502: 39 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.6923077  P(node) =0.00195
##     class counts:    12    12     9     6     0
##    probabilities: 0.308 0.308 0.231 0.154 0.000 
##   left son=7004 (19 obs) right son=7005 (20 obs)
##   Primary splits:
##       reimbursement2008 < 3120   to the right, improve=1.4732790, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=1.0783480, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7169889, (0 missing)
##       age               < 79.5   to the left,  improve=0.6923077, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6923077, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the right, agree=0.795, adj=0.579, (0 split)
##       depression < 0.5    to the right, agree=0.641, adj=0.263, (0 split)
##       age        < 79.5   to the left,  agree=0.615, adj=0.211, (0 split)
##       diabetes   < 0.5    to the left,  agree=0.615, adj=0.211, (0 split)
##       copd       < 0.5    to the right, agree=0.590, adj=0.158, (0 split)
## 
## Node number 3503: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     0     2     4     1     0
##    probabilities: 0.000 0.286 0.571 0.143 0.000 
## 
## Node number 3520: 40 observations,    complexity param=0.0002788764
##   predicted class=B1  expected loss=0.55  P(node) =0.002
##     class counts:    18    15     5     1     1
##    probabilities: 0.450 0.375 0.125 0.025 0.025 
##   left son=7040 (32 obs) right son=7041 (8 obs)
##   Primary splits:
##       age          < 80.5   to the left,  improve=1.4125000, (0 missing)
##       osteoporosis < 0.5    to the left,  improve=1.0583330, (0 missing)
##       copd         < 0.5    to the left,  improve=0.8022792, (0 missing)
##       depression   < 0.5    to the left,  improve=0.7111111, (0 missing)
##       diabetes     < 0.5    to the left,  improve=0.2933333, (0 missing)
## 
## Node number 3521: 64 observations,    complexity param=0.0002788764
##   predicted class=B2  expected loss=0.5  P(node) =0.0032
##     class counts:    20    32     9     3     0
##    probabilities: 0.312 0.500 0.141 0.047 0.000 
##   left son=7042 (52 obs) right son=7043 (12 obs)
##   Primary splits:
##       reimbursement2008 < 2565   to the right, improve=1.3052880, (0 missing)
##       age               < 72     to the right, improve=1.1374010, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6240303, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.4687500, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.4238501, (0 missing)
## 
## Node number 3522: 12 observations
##   predicted class=B2  expected loss=0.4166667  P(node) =0.0006
##     class counts:     4     7     1     0     0
##    probabilities: 0.333 0.583 0.083 0.000 0.000 
## 
## Node number 3523: 26 observations,    complexity param=0.0001521144
##   predicted class=B3  expected loss=0.5384615  P(node) =0.0013
##     class counts:     7     7    12     0     0
##    probabilities: 0.269 0.269 0.462 0.000 0.000 
##   left son=7046 (19 obs) right son=7047 (7 obs)
##   Primary splits:
##       diabetes          < 0.5    to the right, improve=2.3464430, (0 missing)
##       copd              < 0.5    to the left,  improve=1.3088490, (0 missing)
##       reimbursement2008 < 2640   to the right, improve=1.3088490, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.9423077, (0 missing)
##       age               < 68     to the left,  improve=0.7707391, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2620   to the right, agree=0.885, adj=0.571, (0 split)
##       copd              < 0.5    to the left,  agree=0.769, adj=0.143, (0 split)
## 
## Node number 3554: 11 observations
##   predicted class=B1  expected loss=0.1818182  P(node) =0.00055
##     class counts:     9     2     0     0     0
##    probabilities: 0.818 0.182 0.000 0.000 0.000 
## 
## Node number 3555: 18 observations
##   predicted class=B2  expected loss=0.6111111  P(node) =0.0009
##     class counts:     5     7     4     1     1
##    probabilities: 0.278 0.389 0.222 0.056 0.056 
## 
## Node number 3590: 23 observations
##   predicted class=B1  expected loss=0.3913043  P(node) =0.00115
##     class counts:    14     6     2     1     0
##    probabilities: 0.609 0.261 0.087 0.043 0.000 
## 
## Node number 3591: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     2     4     1     0     0
##    probabilities: 0.286 0.571 0.143 0.000 0.000 
## 
## Node number 3594: 56 observations
##   predicted class=B1  expected loss=0.375  P(node) =0.0028
##     class counts:    35    15     3     2     1
##    probabilities: 0.625 0.268 0.054 0.036 0.018 
## 
## Node number 3595: 11 observations
##   predicted class=B2  expected loss=0.6363636  P(node) =0.00055
##     class counts:     3     4     3     1     0
##    probabilities: 0.273 0.364 0.273 0.091 0.000 
## 
## Node number 3596: 8 observations
##   predicted class=B1  expected loss=0.125  P(node) =0.0004
##     class counts:     7     1     0     0     0
##    probabilities: 0.875 0.125 0.000 0.000 0.000 
## 
## Node number 3597: 97 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.4639175  P(node) =0.00485
##     class counts:    52    26    17     2     0
##    probabilities: 0.536 0.268 0.175 0.021 0.000 
##   left son=7194 (79 obs) right son=7195 (18 obs)
##   Primary splits:
##       age               < 81.5   to the left,  improve=2.2155960, (0 missing)
##       reimbursement2008 < 5125   to the right, improve=1.6287330, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8331981, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.7669320, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.2559504, (0 missing)
## 
## Node number 3610: 22 observations
##   predicted class=B2  expected loss=0.4090909  P(node) =0.0011
##     class counts:     7    13     1     1     0
##    probabilities: 0.318 0.591 0.045 0.045 0.000 
## 
## Node number 3611: 12 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0006
##     class counts:     6     3     2     1     0
##    probabilities: 0.500 0.250 0.167 0.083 0.000 
## 
## Node number 3644: 7 observations
##   predicted class=B2  expected loss=0.1428571  P(node) =0.00035
##     class counts:     1     6     0     0     0
##    probabilities: 0.143 0.857 0.000 0.000 0.000 
## 
## Node number 3645: 15 observations
##   predicted class=B1  expected loss=0.6  P(node) =0.00075
##     class counts:     6     5     3     1     0
##    probabilities: 0.400 0.333 0.200 0.067 0.000 
## 
## Node number 3646: 9 observations
##   predicted class=B1  expected loss=0.5555556  P(node) =0.00045
##     class counts:     4     3     1     1     0
##    probabilities: 0.444 0.333 0.111 0.111 0.000 
## 
## Node number 3647: 23 observations
##   predicted class=B3  expected loss=0.4782609  P(node) =0.00115
##     class counts:     7     4    12     0     0
##    probabilities: 0.304 0.174 0.522 0.000 0.000 
## 
## Node number 3750: 13 observations
##   predicted class=B2  expected loss=0.1538462  P(node) =0.00065
##     class counts:     2    11     0     0     0
##    probabilities: 0.154 0.846 0.000 0.000 0.000 
## 
## Node number 3751: 25 observations,    complexity param=7.60572e-05
##   predicted class=B2  expected loss=0.48  P(node) =0.00125
##     class counts:     6    13     4     2     0
##    probabilities: 0.240 0.520 0.160 0.080 0.000 
##   left son=7502 (10 obs) right son=7503 (15 obs)
##   Primary splits:
##       reimbursement2008 < 5090   to the left,  improve=1.2666670, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.4558824, (0 missing)
##       age               < 71.5   to the left,  improve=0.3461538, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3174603, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.2500000, (0 missing)
##   Surrogate splits:
##       age       < 71.5   to the right, agree=0.72, adj=0.3, (0 split)
##       cancer    < 0.5    to the left,  agree=0.72, adj=0.3, (0 split)
##       arthritis < 0.5    to the right, agree=0.64, adj=0.1, (0 split)
## 
## Node number 3758: 25 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.52  P(node) =0.00125
##     class counts:     5    12     6     2     0
##    probabilities: 0.200 0.480 0.240 0.080 0.000 
##   left son=7516 (18 obs) right son=7517 (7 obs)
##   Primary splits:
##       reimbursement2008 < 19195  to the left,  improve=0.7828571, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=0.7828571, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.5733333, (0 missing)
##       age               < 71.5   to the right, improve=0.5370588, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.0374359, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the left,  agree=1.00, adj=1.000, (0 split)
##       cancer     < 0.5    to the left,  agree=0.80, adj=0.286, (0 split)
##       age        < 69.5   to the right, agree=0.76, adj=0.143, (0 split)
##       stroke     < 0.5    to the left,  agree=0.76, adj=0.143, (0 split)
## 
## Node number 3759: 14 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.0007
##     class counts:     4     1     8     1     0
##    probabilities: 0.286 0.071 0.571 0.071 0.000 
## 
## Node number 3824: 15 observations
##   predicted class=B1  expected loss=0.4666667  P(node) =0.00075
##     class counts:     8     4     3     0     0
##    probabilities: 0.533 0.267 0.200 0.000 0.000 
## 
## Node number 3825: 15 observations
##   predicted class=B2  expected loss=0.5333333  P(node) =0.00075
##     class counts:     3     7     2     3     0
##    probabilities: 0.200 0.467 0.133 0.200 0.000 
## 
## Node number 3840: 8 observations
##   predicted class=B1  expected loss=0.375  P(node) =0.0004
##     class counts:     5     2     1     0     0
##    probabilities: 0.625 0.250 0.125 0.000 0.000 
## 
## Node number 3841: 24 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4583333  P(node) =0.0012
##     class counts:    10    13     1     0     0
##    probabilities: 0.417 0.542 0.042 0.000 0.000 
##   left son=7682 (7 obs) right son=7683 (17 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=0.38025210, (0 missing)
##       reimbursement2008 < 6890   to the right, improve=0.35000000, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.17222220, (0 missing)
##       age               < 67.5   to the right, improve=0.12500000, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.02731092, (0 missing)
##   Surrogate splits:
##       age           < 66.5   to the left,  agree=0.75, adj=0.143, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.75, adj=0.143, (0 split)
## 
## Node number 3842: 19 observations
##   predicted class=B1  expected loss=0.2105263  P(node) =0.00095
##     class counts:    15     1     3     0     0
##    probabilities: 0.789 0.053 0.158 0.000 0.000 
## 
## Node number 3843: 104 observations,    complexity param=0.0003422574
##   predicted class=B1  expected loss=0.5480769  P(node) =0.0052
##     class counts:    47    31    23     3     0
##    probabilities: 0.452 0.298 0.221 0.029 0.000 
##   left son=7686 (76 obs) right son=7687 (28 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=2.6920190, (0 missing)
##       reimbursement2008 < 3815   to the left,  improve=2.1500750, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9947414, (0 missing)
##       age               < 45.5   to the left,  improve=0.6525368, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5917679, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4710   to the left,  agree=0.769, adj=0.143, (0 split)
##       stroke            < 0.5    to the left,  agree=0.740, adj=0.036, (0 split)
## 
## Node number 3848: 7 observations
##   predicted class=B1  expected loss=0.1428571  P(node) =0.00035
##     class counts:     6     1     0     0     0
##    probabilities: 0.857 0.143 0.000 0.000 0.000 
## 
## Node number 3849: 24 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5833333  P(node) =0.0012
##     class counts:     6    10     2     5     1
##    probabilities: 0.250 0.417 0.083 0.208 0.042 
##   left son=7698 (9 obs) right son=7699 (15 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=1.2611110, (0 missing)
##       age               < 58.5   to the left,  improve=1.2083330, (0 missing)
##       reimbursement2008 < 24480  to the left,  improve=0.9488796, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7083333, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3119048, (0 missing)
##   Surrogate splits:
##       age               < 50.5   to the left,  agree=0.708, adj=0.222, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.667, adj=0.111, (0 split)
##       reimbursement2008 < 19645  to the right, agree=0.667, adj=0.111, (0 split)
##       bucket2008        < 3.5    to the right, agree=0.667, adj=0.111, (0 split)
## 
## Node number 3850: 13 observations
##   predicted class=B3  expected loss=0.5384615  P(node) =0.00065
##     class counts:     2     3     6     2     0
##    probabilities: 0.154 0.231 0.462 0.154 0.000 
## 
## Node number 3851: 8 observations
##   predicted class=B4  expected loss=0.625  P(node) =0.0004
##     class counts:     2     2     1     3     0
##    probabilities: 0.250 0.250 0.125 0.375 0.000 
## 
## Node number 3856: 117 observations,    complexity param=0.0003295812
##   predicted class=B1  expected loss=0.4786325  P(node) =0.00585
##     class counts:    61    35    13     8     0
##    probabilities: 0.521 0.299 0.111 0.068 0.000 
##   left son=7712 (11 obs) right son=7713 (106 obs)
##   Primary splits:
##       reimbursement2008 < 5335   to the left,  improve=1.6681470, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.5859199, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5517094, (0 missing)
##       age               < 82.5   to the left,  improve=0.5042735, (0 missing)
##       copd              < 0.5    to the right, improve=0.4257959, (0 missing)
## 
## Node number 3857: 27 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.4814815  P(node) =0.00135
##     class counts:    10    14     2     1     0
##    probabilities: 0.370 0.519 0.074 0.037 0.000 
##   left son=7714 (13 obs) right son=7715 (14 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the right, improve=1.1925110, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.0740740, (0 missing)
##       reimbursement2008 < 8000   to the left,  improve=0.6980057, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.6980057, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3386940, (0 missing)
##   Surrogate splits:
##       alzheimers        < 0.5    to the left,  agree=0.667, adj=0.308, (0 split)
##       ihd               < 0.5    to the right, agree=0.593, adj=0.154, (0 split)
##       reimbursement2008 < 7825   to the right, agree=0.593, adj=0.154, (0 split)
##       bucket2008        < 3.5    to the right, agree=0.593, adj=0.154, (0 split)
##       age               < 71.5   to the right, agree=0.556, adj=0.077, (0 split)
## 
## Node number 3858: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     1     5     1     0     0
##    probabilities: 0.143 0.714 0.143 0.000 0.000 
## 
## Node number 3859: 19 observations
##   predicted class=B3  expected loss=0.6315789  P(node) =0.00095
##     class counts:     6     4     7     1     1
##    probabilities: 0.316 0.211 0.368 0.053 0.053 
## 
## Node number 3860: 17 observations
##   predicted class=B1  expected loss=0.2941176  P(node) =0.00085
##     class counts:    12     2     1     2     0
##    probabilities: 0.706 0.118 0.059 0.118 0.000 
## 
## Node number 3861: 11 observations
##   predicted class=B2  expected loss=0.3636364  P(node) =0.00055
##     class counts:     3     7     0     0     1
##    probabilities: 0.273 0.636 0.000 0.000 0.091 
## 
## Node number 3862: 61 observations,    complexity param=0.0004056384
##   predicted class=B2  expected loss=0.4262295  P(node) =0.00305
##     class counts:    14    35    10     2     0
##    probabilities: 0.230 0.574 0.164 0.033 0.000 
##   left son=7724 (14 obs) right son=7725 (47 obs)
##   Primary splits:
##       reimbursement2008 < 14285  to the right, improve=2.9027360, (0 missing)
##       age               < 81.5   to the left,  improve=2.7429190, (0 missing)
##       stroke            < 0.5    to the right, improve=0.7350427, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6774892, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.6382429, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.869, adj=0.429, (0 split)
## 
## Node number 3863: 68 observations,    complexity param=0.0004056384
##   predicted class=B2  expected loss=0.6617647  P(node) =0.0034
##     class counts:    20    23    16     8     1
##    probabilities: 0.294 0.338 0.235 0.118 0.015 
##   left son=7726 (49 obs) right son=7727 (19 obs)
##   Primary splits:
##       reimbursement2008 < 7090   to the right, improve=2.0709230, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.9533610, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.8022620, (0 missing)
##       copd              < 0.5    to the left,  improve=1.4319330, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.9282531, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.926, adj=0.737, (0 split)
##       age        < 87.5   to the left,  agree=0.735, adj=0.053, (0 split)
## 
## Node number 3864: 50 observations
##   predicted class=B2  expected loss=0.3  P(node) =0.0025
##     class counts:    11    35     2     2     0
##    probabilities: 0.220 0.700 0.040 0.040 0.000 
## 
## Node number 3865: 14 observations
##   predicted class=B1  expected loss=0.5714286  P(node) =0.0007
##     class counts:     6     3     5     0     0
##    probabilities: 0.429 0.214 0.357 0.000 0.000 
## 
## Node number 3870: 37 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.6216216  P(node) =0.00185
##     class counts:    14    14     6     3     0
##    probabilities: 0.378 0.378 0.162 0.081 0.000 
##   left son=7740 (17 obs) right son=7741 (20 obs)
##   Primary splits:
##       reimbursement2008 < 4035   to the left,  improve=1.0186010, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6996787, (0 missing)
##       age               < 87.5   to the right, improve=0.6571379, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6256971, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.5308041, (0 missing)
##   Surrogate splits:
##       age           < 90.5   to the right, agree=0.595, adj=0.118, (0 split)
##       copd          < 0.5    to the left,  agree=0.595, adj=0.118, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.568, adj=0.059, (0 split)
## 
## Node number 3871: 67 observations
##   predicted class=B2  expected loss=0.4179104  P(node) =0.00335
##     class counts:    14    39    12     2     0
##    probabilities: 0.209 0.582 0.179 0.030 0.000 
## 
## Node number 3892: 16 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0008
##     class counts:     8     4     2     2     0
##    probabilities: 0.500 0.250 0.125 0.125 0.000 
## 
## Node number 3893: 33 observations,    complexity param=0.0004563432
##   predicted class=B3  expected loss=0.5757576  P(node) =0.00165
##     class counts:     8     9    14     2     0
##    probabilities: 0.242 0.273 0.424 0.061 0.000 
##   left son=7786 (11 obs) right son=7787 (22 obs)
##   Primary splits:
##       reimbursement2008 < 5825   to the left,  improve=2.0909090, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.5680110, (0 missing)
##       age               < 66.5   to the right, improve=1.4575420, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.3232320, (0 missing)
##       depression        < 0.5    to the left,  improve=0.8073593, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.788, adj=0.364, (0 split)
##       ihd        < 0.5    to the left,  agree=0.758, adj=0.273, (0 split)
## 
## Node number 3894: 33 observations,    complexity param=7.60572e-05
##   predicted class=B3  expected loss=0.5757576  P(node) =0.00165
##     class counts:     7     9    14     3     0
##    probabilities: 0.212 0.273 0.424 0.091 0.000 
##   left son=7788 (26 obs) right son=7789 (7 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=1.4748580, (0 missing)
##       copd              < 0.5    to the left,  improve=1.3210120, (0 missing)
##       reimbursement2008 < 14730  to the left,  improve=0.7056277, (0 missing)
##       age               < 76.5   to the right, improve=0.6905901, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5151515, (0 missing)
## 
## Node number 3895: 30 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4333333  P(node) =0.0015
##     class counts:     1    17     8     4     0
##    probabilities: 0.033 0.567 0.267 0.133 0.000 
##   left son=7790 (13 obs) right son=7791 (17 obs)
##   Primary splits:
##       age               < 75.5   to the left,  improve=2.7164400, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.2202380, (0 missing)
##       reimbursement2008 < 6230   to the left,  improve=1.0828160, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.6236045, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4896332, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4310   to the left,  agree=0.700, adj=0.308, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.667, adj=0.231, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.600, adj=0.077, (0 split)
##       stroke            < 0.5    to the right, agree=0.600, adj=0.077, (0 split)
## 
## Node number 3936: 30 observations
##   predicted class=B1  expected loss=0.4333333  P(node) =0.0015
##     class counts:    17    10     1     1     1
##    probabilities: 0.567 0.333 0.033 0.033 0.033 
## 
## Node number 3937: 8 observations
##   predicted class=B4  expected loss=0.625  P(node) =0.0004
##     class counts:     2     2     1     3     0
##    probabilities: 0.250 0.250 0.125 0.375 0.000 
## 
## Node number 3940: 59 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.4915254  P(node) =0.00295
##     class counts:    19    30     6     3     1
##    probabilities: 0.322 0.508 0.102 0.051 0.017 
##   left son=7880 (7 obs) right son=7881 (52 obs)
##   Primary splits:
##       reimbursement2008 < 4180   to the left,  improve=2.3199850, (0 missing)
##       age               < 74.5   to the right, improve=1.6846670, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7680925, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4469662, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.3751074, (0 missing)
## 
## Node number 3941: 26 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.6923077  P(node) =0.0013
##     class counts:     8     8     5     5     0
##    probabilities: 0.308 0.308 0.192 0.192 0.000 
##   left son=7882 (18 obs) right son=7883 (8 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=1.5705130, (0 missing)
##       age               < 90.5   to the right, improve=1.5147480, (0 missing)
##       reimbursement2008 < 5065   to the left,  improve=1.3038460, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5586081, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5072296, (0 missing)
##   Surrogate splits:
##       copd < 0.5    to the left,  agree=0.731, adj=0.125, (0 split)
## 
## Node number 3942: 32 observations
##   predicted class=B2  expected loss=0.34375  P(node) =0.0016
##     class counts:     1    21     4     6     0
##    probabilities: 0.031 0.656 0.125 0.187 0.000 
## 
## Node number 3943: 10 observations
##   predicted class=B1  expected loss=0.7  P(node) =0.0005
##     class counts:     3     2     2     3     0
##    probabilities: 0.300 0.200 0.200 0.300 0.000 
## 
## Node number 3946: 10 observations
##   predicted class=B2  expected loss=0.4  P(node) =0.0005
##     class counts:     2     6     0     2     0
##    probabilities: 0.200 0.600 0.000 0.200 0.000 
## 
## Node number 3947: 11 observations
##   predicted class=B4  expected loss=0.5454545  P(node) =0.00055
##     class counts:     2     3     1     5     0
##    probabilities: 0.182 0.273 0.091 0.455 0.000 
## 
## Node number 3950: 23 observations
##   predicted class=B2  expected loss=0.3043478  P(node) =0.00115
##     class counts:     2    16     3     2     0
##    probabilities: 0.087 0.696 0.130 0.087 0.000 
## 
## Node number 3951: 22 observations,    complexity param=0.0001521144
##   predicted class=B3  expected loss=0.5  P(node) =0.0011
##     class counts:     3     8    11     0     0
##    probabilities: 0.136 0.364 0.500 0.000 0.000 
##   left son=7902 (15 obs) right son=7903 (7 obs)
##   Primary splits:
##       reimbursement2008 < 6650   to the right, improve=2.0008660, (0 missing)
##       copd              < 0.5    to the right, improve=1.9246750, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.7630150, (0 missing)
##       age               < 72.5   to the left,  improve=0.9722944, (0 missing)
##   Surrogate splits:
##       age           < 64.5   to the right, agree=0.727, adj=0.143, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.727, adj=0.143, (0 split)
##       ihd           < 0.5    to the right, agree=0.727, adj=0.143, (0 split)
##       stroke        < 0.5    to the left,  agree=0.727, adj=0.143, (0 split)
## 
## Node number 3956: 52 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.4230769  P(node) =0.0026
##     class counts:     8    30    10     4     0
##    probabilities: 0.154 0.577 0.192 0.077 0.000 
##   left son=7912 (30 obs) right son=7913 (22 obs)
##   Primary splits:
##       reimbursement2008 < 23850  to the left,  improve=3.0974360, (0 missing)
##       age               < 77.5   to the right, improve=1.7192480, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=1.1057690, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8778281, (0 missing)
##       cancer            < 0.5    to the right, improve=0.6335470, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the left,  agree=0.731, adj=0.364, (0 split)
##       cancer     < 0.5    to the left,  agree=0.615, adj=0.091, (0 split)
##       age        < 59     to the right, agree=0.596, adj=0.045, (0 split)
##       stroke     < 0.5    to the left,  agree=0.596, adj=0.045, (0 split)
## 
## Node number 3957: 164 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5853659  P(node) =0.0082
##     class counts:    34    68    46    14     2
##    probabilities: 0.207 0.415 0.280 0.085 0.012 
##   left son=7914 (90 obs) right son=7915 (74 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=1.4857980, (0 missing)
##       reimbursement2008 < 4235   to the right, improve=1.2625250, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.1619200, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.0523830, (0 missing)
##       age               < 89.5   to the right, improve=0.8063318, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 9795   to the left,  agree=0.604, adj=0.122, (0 split)
##       copd              < 0.5    to the left,  agree=0.598, adj=0.108, (0 split)
##       age               < 85.5   to the left,  agree=0.585, adj=0.081, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.585, adj=0.081, (0 split)
##       ihd               < 0.5    to the right, agree=0.579, adj=0.068, (0 split)
## 
## Node number 3968: 11 observations
##   predicted class=B1  expected loss=0.2727273  P(node) =0.00055
##     class counts:     8     0     3     0     0
##    probabilities: 0.727 0.000 0.273 0.000 0.000 
## 
## Node number 3969: 32 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.6875  P(node) =0.0016
##     class counts:    10     9     9     2     2
##    probabilities: 0.312 0.281 0.281 0.062 0.062 
##   left son=7938 (24 obs) right son=7939 (8 obs)
##   Primary splits:
##       age               < 96.5   to the left,  improve=1.8958330, (0 missing)
##       copd              < 0.5    to the right, improve=1.4291670, (0 missing)
##       reimbursement2008 < 10790  to the right, improve=0.8539286, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6875000, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3878968, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 10790  to the right, agree=0.781, adj=0.125, (0 split)
## 
## Node number 3970: 8 observations
##   predicted class=B2  expected loss=0.25  P(node) =0.0004
##     class counts:     0     6     2     0     0
##    probabilities: 0.000 0.750 0.250 0.000 0.000 
## 
## Node number 3971: 16 observations
##   predicted class=B3  expected loss=0.5625  P(node) =0.0008
##     class counts:     4     3     7     2     0
##    probabilities: 0.250 0.188 0.438 0.125 0.000 
## 
## Node number 3974: 177 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6101695  P(node) =0.00885
##     class counts:    46    69    25    32     5
##    probabilities: 0.260 0.390 0.141 0.181 0.028 
##   left son=7948 (169 obs) right son=7949 (8 obs)
##   Primary splits:
##       reimbursement2008 < 14365  to the left,  improve=2.4954790, (0 missing)
##       age               < 75.5   to the right, improve=1.9376320, (0 missing)
##       stroke            < 0.5    to the right, improve=0.7544507, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.6832293, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.5905001, (0 missing)
## 
## Node number 3975: 91 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6483516  P(node) =0.00455
##     class counts:    14    32    24    18     3
##    probabilities: 0.154 0.352 0.264 0.198 0.033 
##   left son=7950 (34 obs) right son=7951 (57 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=1.981073, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.924030, (0 missing)
##       depression        < 0.5    to the left,  improve=1.545458, (0 missing)
##       reimbursement2008 < 9695   to the right, improve=1.218681, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.168681, (0 missing)
##   Surrogate splits:
##       ihd < 0.5    to the left,  agree=0.67, adj=0.118, (0 split)
## 
## Node number 3980: 210 observations,    complexity param=0.0003650745
##   predicted class=B2  expected loss=0.6047619  P(node) =0.0105
##     class counts:    44    83    47    31     5
##    probabilities: 0.210 0.395 0.224 0.148 0.024 
##   left son=7960 (48 obs) right son=7961 (162 obs)
##   Primary splits:
##       age               < 81.5   to the right, improve=1.422399, (0 missing)
##       ihd               < 0.5    to the right, improve=1.305861, (0 missing)
##       reimbursement2008 < 4080   to the left,  improve=1.052847, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.007552, (0 missing)
##       depression        < 0.5    to the right, improve=0.922645, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 6050   to the right, agree=0.776, adj=0.021, (0 split)
## 
## Node number 3981: 25 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.52  P(node) =0.00125
##     class counts:     1    10    12     1     1
##    probabilities: 0.040 0.400 0.480 0.040 0.040 
##   left son=7962 (17 obs) right son=7963 (8 obs)
##   Primary splits:
##       reimbursement2008 < 6260   to the right, improve=1.3258820, (0 missing)
##       age               < 67.5   to the right, improve=0.7073016, (0 missing)
##       depression        < 0.5    to the right, improve=0.4661538, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4576623, (0 missing)
##       copd              < 0.5    to the right, improve=0.2588889, (0 missing)
##   Surrogate splits:
##       age < 75     to the left,  agree=0.72, adj=0.125, (0 split)
## 
## Node number 4008: 19 observations
##   predicted class=B2  expected loss=0.2631579  P(node) =0.00095
##     class counts:     2    14     1     2     0
##    probabilities: 0.105 0.737 0.053 0.105 0.000 
## 
## Node number 4009: 69 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.4782609  P(node) =0.00345
##     class counts:    14    36    13     5     1
##    probabilities: 0.203 0.522 0.188 0.072 0.014 
##   left son=8018 (29 obs) right son=8019 (40 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=1.4558970, (0 missing)
##       age               < 81.5   to the right, improve=1.2755920, (0 missing)
##       reimbursement2008 < 3895   to the left,  improve=1.2388600, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6811594, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6025765, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 3955   to the left,  agree=0.667, adj=0.207, (0 split)
##       age               < 93     to the right, agree=0.623, adj=0.103, (0 split)
##       depression        < 0.5    to the right, agree=0.623, adj=0.103, (0 split)
## 
## Node number 4024: 13 observations
##   predicted class=B2  expected loss=0.5384615  P(node) =0.00065
##     class counts:     3     6     2     2     0
##    probabilities: 0.231 0.462 0.154 0.154 0.000 
## 
## Node number 4025: 22 observations
##   predicted class=B3  expected loss=0.5454545  P(node) =0.0011
##     class counts:     4     5    10     3     0
##    probabilities: 0.182 0.227 0.455 0.136 0.000 
## 
## Node number 4026: 187 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5347594  P(node) =0.00935
##     class counts:    20    87    53    22     5
##    probabilities: 0.107 0.465 0.283 0.118 0.027 
##   left son=8052 (35 obs) right son=8053 (152 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=0.9804330, (0 missing)
##       reimbursement2008 < 7580   to the right, improve=0.9500758, (0 missing)
##       age               < 75.5   to the left,  improve=0.9208236, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8858296, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.6009844, (0 missing)
## 
## Node number 4027: 31 observations
##   predicted class=B2  expected loss=0.4516129  P(node) =0.00155
##     class counts:     2    17     4     8     0
##    probabilities: 0.065 0.548 0.129 0.258 0.000 
## 
## Node number 4064: 59 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.6610169  P(node) =0.00295
##     class counts:    20    12    12    15     0
##    probabilities: 0.339 0.203 0.203 0.254 0.000 
##   left son=8128 (10 obs) right son=8129 (49 obs)
##   Primary splits:
##       stroke            < 0.5    to the right, improve=2.0111380, (0 missing)
##       cancer            < 0.5    to the right, improve=1.1459910, (0 missing)
##       reimbursement2008 < 19645  to the right, improve=1.0270110, (0 missing)
##       age               < 80     to the left,  improve=0.9767058, (0 missing)
##       depression        < 0.5    to the right, improve=0.7631860, (0 missing)
## 
## Node number 4065: 8 observations
##   predicted class=B3  expected loss=0.375  P(node) =0.0004
##     class counts:     2     0     5     1     0
##    probabilities: 0.250 0.000 0.625 0.125 0.000 
## 
## Node number 4066: 9 observations
##   predicted class=B1  expected loss=0.6666667  P(node) =0.00045
##     class counts:     3     1     3     2     0
##    probabilities: 0.333 0.111 0.333 0.222 0.000 
## 
## Node number 4067: 19 observations
##   predicted class=B2  expected loss=0.4736842  P(node) =0.00095
##     class counts:     2    10     0     7     0
##    probabilities: 0.105 0.526 0.000 0.368 0.000 
## 
## Node number 4068: 32 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.40625  P(node) =0.0016
##     class counts:     4    19     4     3     2
##    probabilities: 0.125 0.594 0.125 0.094 0.062 
##   left son=8136 (7 obs) right son=8137 (25 obs)
##   Primary splits:
##       reimbursement2008 < 25510  to the right, improve=3.0153570, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.3731060, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9474206, (0 missing)
##       age               < 72.5   to the right, improve=0.6125000, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.4791667, (0 missing)
## 
## Node number 4069: 9 observations
##   predicted class=B1  expected loss=0.6666667  P(node) =0.00045
##     class counts:     3     1     2     1     2
##    probabilities: 0.333 0.111 0.222 0.111 0.222 
## 
## Node number 4070: 81 observations,    complexity param=0.000380286
##   predicted class=B2  expected loss=0.654321  P(node) =0.00405
##     class counts:    14    28    18    18     3
##    probabilities: 0.173 0.346 0.222 0.222 0.037 
##   left son=8140 (35 obs) right son=8141 (46 obs)
##   Primary splits:
##       age               < 73.5   to the left,  improve=1.8360860, (0 missing)
##       reimbursement2008 < 18450  to the right, improve=1.8267530, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.4464610, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.6743146, (0 missing)
##       bucket2008        < 3.5    to the right, improve=0.6083053, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 18450  to the right, agree=0.741, adj=0.400, (0 split)
##       bucket2008        < 3.5    to the right, agree=0.728, adj=0.371, (0 split)
##       osteoporosis      < 0.5    to the right, agree=0.654, adj=0.200, (0 split)
##       cancer            < 0.5    to the right, agree=0.580, adj=0.029, (0 split)
##       depression        < 0.5    to the left,  agree=0.580, adj=0.029, (0 split)
## 
## Node number 4071: 16 observations
##   predicted class=B4  expected loss=0.5  P(node) =0.0008
##     class counts:     0     2     5     8     1
##    probabilities: 0.000 0.125 0.312 0.500 0.062 
## 
## Node number 4072: 36 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5277778  P(node) =0.0018
##     class counts:     4    17    13     0     2
##    probabilities: 0.111 0.472 0.361 0.000 0.056 
##   left son=8144 (29 obs) right son=8145 (7 obs)
##   Primary splits:
##       reimbursement2008 < 22930  to the right, improve=1.4020250, (0 missing)
##       age               < 70.5   to the left,  improve=1.0793650, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.3754730, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3367677, (0 missing)
##       cancer            < 0.5    to the right, improve=0.2222222, (0 missing)
## 
## Node number 4073: 89 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5842697  P(node) =0.00445
##     class counts:    13    37    19    16     4
##    probabilities: 0.146 0.416 0.213 0.180 0.045 
##   left son=8146 (55 obs) right son=8147 (34 obs)
##   Primary splits:
##       reimbursement2008 < 17640  to the right, improve=1.6152980, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.1922490, (0 missing)
##       age               < 83.5   to the left,  improve=1.1121530, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.0048700, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9641839, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.775, adj=0.412, (0 split)
## 
## Node number 4088: 30 observations
##   predicted class=B2  expected loss=0.3333333  P(node) =0.0015
##     class counts:     2    20     2     4     2
##    probabilities: 0.067 0.667 0.067 0.133 0.067 
## 
## Node number 4089: 17 observations
##   predicted class=B3  expected loss=0.5294118  P(node) =0.00085
##     class counts:     1     5     8     2     1
##    probabilities: 0.059 0.294 0.471 0.118 0.059 
## 
## Node number 4090: 11 observations
##   predicted class=B2  expected loss=0.3636364  P(node) =0.00055
##     class counts:     1     7     2     1     0
##    probabilities: 0.091 0.636 0.182 0.091 0.000 
## 
## Node number 4091: 33 observations,    complexity param=0.0002662002
##   predicted class=B4  expected loss=0.5757576  P(node) =0.00165
##     class counts:     2    12     5    14     0
##    probabilities: 0.061 0.364 0.152 0.424 0.000 
##   left son=8182 (17 obs) right son=8183 (16 obs)
##   Primary splits:
##       arthritis         < 0.5    to the right, improve=1.3990640, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.8990642, (0 missing)
##       reimbursement2008 < 28890  to the right, improve=0.8332194, (0 missing)
##       age               < 66.5   to the right, improve=0.6404040, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3459596, (0 missing)
##   Surrogate splits:
##       age               < 60.5   to the right, agree=0.636, adj=0.250, (0 split)
##       cancer            < 0.5    to the right, agree=0.636, adj=0.250, (0 split)
##       reimbursement2008 < 28890  to the right, agree=0.636, adj=0.250, (0 split)
##       copd              < 0.5    to the right, agree=0.576, adj=0.125, (0 split)
##       depression        < 0.5    to the right, agree=0.576, adj=0.125, (0 split)
## 
## Node number 4092: 26 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.6538462  P(node) =0.0013
##     class counts:     6     9     5     5     1
##    probabilities: 0.231 0.346 0.192 0.192 0.038 
##   left son=8184 (13 obs) right son=8185 (13 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=2.4615380, (0 missing)
##       age               < 77.5   to the left,  improve=0.8995726, (0 missing)
##       reimbursement2008 < 45075  to the right, improve=0.8134615, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6061307, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.4615385, (0 missing)
##   Surrogate splits:
##       age               < 72.5   to the left,  agree=0.615, adj=0.231, (0 split)
##       reimbursement2008 < 41035  to the left,  agree=0.615, adj=0.231, (0 split)
##       bucket2008        < 4.5    to the left,  agree=0.577, adj=0.154, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.538, adj=0.077, (0 split)
##       arthritis         < 0.5    to the left,  agree=0.538, adj=0.077, (0 split)
## 
## Node number 4093: 71 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5774648  P(node) =0.00355
##     class counts:     0    30    12    23     6
##    probabilities: 0.000 0.423 0.169 0.324 0.085 
##   left son=8186 (13 obs) right son=8187 (58 obs)
##   Primary splits:
##       reimbursement2008 < 38625  to the left,  improve=1.735906, (0 missing)
##       age               < 79.5   to the left,  improve=1.085709, (0 missing)
##       bucket2008        < 4.5    to the left,  improve=1.083189, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.081118, (0 missing)
##       cancer            < 0.5    to the right, improve=0.997176, (0 missing)
##   Surrogate splits:
##       age < 86.5   to the right, agree=0.831, adj=0.077, (0 split)
## 
## Node number 4094: 180 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.7  P(node) =0.009
##     class counts:    14    54    53    51     8
##    probabilities: 0.078 0.300 0.294 0.283 0.044 
##   left son=8188 (150 obs) right son=8189 (30 obs)
##   Primary splits:
##       age               < 82.5   to the left,  improve=1.8600000, (0 missing)
##       reimbursement2008 < 101155 to the left,  improve=1.3289020, (0 missing)
##       bucket2008        < 4.5    to the right, improve=1.0857140, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.9828717, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.9785714, (0 missing)
## 
## Node number 4095: 54 observations,    complexity param=0.0001521144
##   predicted class=B4  expected loss=0.5185185  P(node) =0.0027
##     class counts:     4    11    10    26     3
##    probabilities: 0.074 0.204 0.185 0.481 0.056 
##   left son=8190 (39 obs) right son=8191 (15 obs)
##   Primary splits:
##       reimbursement2008 < 35865  to the left,  improve=2.7310540, (0 missing)
##       age               < 83.5   to the right, improve=1.5895620, (0 missing)
##       depression        < 0.5    to the right, improve=1.0054170, (0 missing)
##       cancer            < 0.5    to the right, improve=0.8050992, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4588930, (0 missing)
## 
## Node number 5142: 398 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1758794  P(node) =0.0199
##     class counts:   328    39    26     3     2
##    probabilities: 0.824 0.098 0.065 0.008 0.005 
##   left son=10284 (321 obs) right son=10285 (77 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=0.5824155, (0 missing)
##       age               < 86.5   to the left,  improve=0.5329233, (0 missing)
##       reimbursement2008 < 315    to the left,  improve=0.4958627, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3680496, (0 missing)
##       depression        < 0.5    to the left,  improve=0.2599538, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.809, adj=0.013, (0 split)
## 
## Node number 5143: 32 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.28125  P(node) =0.0016
##     class counts:    23     8     0     1     0
##    probabilities: 0.719 0.250 0.000 0.031 0.000 
##   left son=10286 (10 obs) right son=10287 (22 obs)
##   Primary splits:
##       age               < 83.5   to the right, improve=0.81931820, (0 missing)
##       reimbursement2008 < 485    to the right, improve=0.04142157, (0 missing)
##       ihd               < 0.5    to the right, improve=0.02035714, (0 missing)
## 
## Node number 5766: 51 observations
##   predicted class=B1  expected loss=0.2941176  P(node) =0.00255
##     class counts:    36     6     7     2     0
##    probabilities: 0.706 0.118 0.137 0.039 0.000 
## 
## Node number 5767: 8 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0004
##     class counts:     3     4     1     0     0
##    probabilities: 0.375 0.500 0.125 0.000 0.000 
## 
## Node number 5768: 79 observations
##   predicted class=B1  expected loss=0.2278481  P(node) =0.00395
##     class counts:    61    11     6     1     0
##    probabilities: 0.772 0.139 0.076 0.013 0.000 
## 
## Node number 5769: 30 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.4333333  P(node) =0.0015
##     class counts:    17    10     3     0     0
##    probabilities: 0.567 0.333 0.100 0.000 0.000 
##   left son=11538 (23 obs) right son=11539 (7 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=2.1370600, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.8333333, (0 missing)
##       reimbursement2008 < 1465   to the right, improve=0.7869048, (0 missing)
##       age               < 75.5   to the right, improve=0.3803922, (0 missing)
## 
## Node number 5786: 9 observations
##   predicted class=B1  expected loss=0.2222222  P(node) =0.00045
##     class counts:     7     1     0     1     0
##    probabilities: 0.778 0.111 0.000 0.111 0.000 
## 
## Node number 5787: 11 observations
##   predicted class=B2  expected loss=0.5454545  P(node) =0.00055
##     class counts:     4     5     1     1     0
##    probabilities: 0.364 0.455 0.091 0.091 0.000 
## 
## Node number 5790: 11 observations
##   predicted class=B1  expected loss=0.4545455  P(node) =0.00055
##     class counts:     6     5     0     0     0
##    probabilities: 0.545 0.455 0.000 0.000 0.000 
## 
## Node number 5791: 9 observations
##   predicted class=B2  expected loss=0.3333333  P(node) =0.00045
##     class counts:     3     6     0     0     0
##    probabilities: 0.333 0.667 0.000 0.000 0.000 
## 
## Node number 5898: 10 observations
##   predicted class=B1  expected loss=0.1  P(node) =0.0005
##     class counts:     9     0     1     0     0
##    probabilities: 0.900 0.000 0.100 0.000 0.000 
## 
## Node number 5899: 127 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3149606  P(node) =0.00635
##     class counts:    87    25    12     3     0
##    probabilities: 0.685 0.197 0.094 0.024 0.000 
##   left son=11798 (8 obs) right son=11799 (119 obs)
##   Primary splits:
##       reimbursement2008 < 875    to the left,  improve=0.6516410, (0 missing)
##       depression        < 0.5    to the right, improve=0.4432881, (0 missing)
##       age               < 91     to the right, improve=0.4331536, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1827812, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.1471502, (0 missing)
## 
## Node number 5902: 7 observations
##   predicted class=B1  expected loss=0.5714286  P(node) =0.00035
##     class counts:     3     2     2     0     0
##    probabilities: 0.429 0.286 0.286 0.000 0.000 
## 
## Node number 5903: 13 observations
##   predicted class=B2  expected loss=0.5384615  P(node) =0.00065
##     class counts:     4     6     2     1     0
##    probabilities: 0.308 0.462 0.154 0.077 0.000 
## 
## Node number 6054: 10 observations
##   predicted class=B1  expected loss=0.1  P(node) =0.0005
##     class counts:     9     1     0     0     0
##    probabilities: 0.900 0.100 0.000 0.000 0.000 
## 
## Node number 6055: 115 observations,    complexity param=6.084576e-05
##   predicted class=B1  expected loss=0.3652174  P(node) =0.00575
##     class counts:    73    29    12     0     1
##    probabilities: 0.635 0.252 0.104 0.000 0.009 
##   left son=12110 (36 obs) right son=12111 (79 obs)
##   Primary splits:
##       age               < 73.5   to the right, improve=0.9624839, (0 missing)
##       reimbursement2008 < 1075   to the right, improve=0.7285649, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6802899, (0 missing)
##       kidney            < 0.5    to the right, improve=0.6593008, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.2298137, (0 missing)
##   Surrogate splits:
##       stroke < 0.5    to the right, agree=0.704, adj=0.056, (0 split)
## 
## Node number 6094: 18 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.0009
##     class counts:     8    10     0     0     0
##    probabilities: 0.444 0.556 0.000 0.000 0.000 
## 
## Node number 6095: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     0     3     4     0     0
##    probabilities: 0.000 0.429 0.571 0.000 0.000 
## 
## Node number 6154: 59 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3389831  P(node) =0.00295
##     class counts:    39    15     4     0     1
##    probabilities: 0.661 0.254 0.068 0.000 0.017 
##   left son=12308 (15 obs) right son=12309 (44 obs)
##   Primary splits:
##       reimbursement2008 < 2050   to the right, improve=1.2428860, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.4978711, (0 missing)
##       age               < 47     to the right, improve=0.3049186, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1023175, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the right, agree=0.78, adj=0.133, (0 split)
## 
## Node number 6155: 10 observations
##   predicted class=B1  expected loss=0.6  P(node) =0.0005
##     class counts:     4     4     2     0     0
##    probabilities: 0.400 0.400 0.200 0.000 0.000 
## 
## Node number 6168: 49 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3877551  P(node) =0.00245
##     class counts:    30    15     4     0     0
##    probabilities: 0.612 0.306 0.082 0.000 0.000 
##   left son=12336 (11 obs) right son=12337 (38 obs)
##   Primary splits:
##       reimbursement2008 < 2155   to the right, improve=0.9152427, (0 missing)
##       age               < 71.5   to the right, improve=0.6536797, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2980178, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.2857143, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.0252905, (0 missing)
## 
## Node number 6169: 9 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.00045
##     class counts:     4     5     0     0     0
##    probabilities: 0.444 0.556 0.000 0.000 0.000 
## 
## Node number 6174: 13 observations
##   predicted class=B2  expected loss=0.6153846  P(node) =0.00065
##     class counts:     4     5     3     1     0
##    probabilities: 0.308 0.385 0.231 0.077 0.000 
## 
## Node number 6175: 8 observations
##   predicted class=B4  expected loss=0.625  P(node) =0.0004
##     class counts:     2     1     2     3     0
##    probabilities: 0.250 0.125 0.250 0.375 0.000 
## 
## Node number 6224: 23 observations
##   predicted class=B1  expected loss=0.2173913  P(node) =0.00115
##     class counts:    18     5     0     0     0
##    probabilities: 0.783 0.217 0.000 0.000 0.000 
## 
## Node number 6225: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     2     5     0     0     0
##    probabilities: 0.286 0.714 0.000 0.000 0.000 
## 
## Node number 6362: 45 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.4888889  P(node) =0.00225
##     class counts:    23    13     8     0     1
##    probabilities: 0.511 0.289 0.178 0.000 0.022 
##   left son=12724 (32 obs) right son=12725 (13 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=1.9146370, (0 missing)
##       age               < 78.5   to the left,  improve=1.5873020, (0 missing)
##       reimbursement2008 < 2165   to the right, improve=1.3407410, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.7235888, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6008354, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2895   to the left,  agree=0.778, adj=0.231, (0 split)
## 
## Node number 6363: 60 observations,    complexity param=0.0002028192
##   predicted class=B2  expected loss=0.6  P(node) =0.003
##     class counts:    21    24    13     2     0
##    probabilities: 0.350 0.400 0.217 0.033 0.000 
##   left son=12726 (36 obs) right son=12727 (24 obs)
##   Primary splits:
##       reimbursement2008 < 2215   to the right, improve=2.1944440, (0 missing)
##       age               < 71.5   to the left,  improve=1.3810440, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7444444, (0 missing)
##       copd              < 0.5    to the right, improve=0.2083333, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.1250000, (0 missing)
##   Surrogate splits:
##       age < 73.5   to the left,  agree=0.633, adj=0.083, (0 split)
## 
## Node number 6670: 42 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.5  P(node) =0.0021
##     class counts:    21    18     2     1     0
##    probabilities: 0.500 0.429 0.048 0.024 0.000 
##   left son=13340 (34 obs) right son=13341 (8 obs)
##   Primary splits:
##       reimbursement2008 < 2305   to the left,  improve=0.8284314, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6695992, (0 missing)
##       age               < 79.5   to the left,  improve=0.5952381, (0 missing)
##       kidney            < 0.5    to the right, improve=0.1919192, (0 missing)
##       copd              < 0.5    to the left,  improve=0.1809524, (0 missing)
## 
## Node number 6671: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     2     5     0     1     0
##    probabilities: 0.250 0.625 0.000 0.125 0.000 
## 
## Node number 6680: 19 observations
##   predicted class=B1  expected loss=0.2631579  P(node) =0.00095
##     class counts:    14     3     2     0     0
##    probabilities: 0.737 0.158 0.105 0.000 0.000 
## 
## Node number 6681: 14 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0007
##     class counts:     5     7     1     0     1
##    probabilities: 0.357 0.500 0.071 0.000 0.071 
## 
## Node number 6682: 12 observations
##   predicted class=B1  expected loss=0.4166667  P(node) =0.0006
##     class counts:     7     5     0     0     0
##    probabilities: 0.583 0.417 0.000 0.000 0.000 
## 
## Node number 6683: 18 observations
##   predicted class=B2  expected loss=0.3333333  P(node) =0.0009
##     class counts:     5    12     1     0     0
##    probabilities: 0.278 0.667 0.056 0.000 0.000 
## 
## Node number 6688: 96 observations
##   predicted class=B1  expected loss=0.3020833  P(node) =0.0048
##     class counts:    67    19     7     3     0
##    probabilities: 0.698 0.198 0.073 0.031 0.000 
## 
## Node number 6689: 115 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.4434783  P(node) =0.00575
##     class counts:    64    32    11     7     1
##    probabilities: 0.557 0.278 0.096 0.061 0.009 
##   left son=13378 (20 obs) right son=13379 (95 obs)
##   Primary splits:
##       age               < 60     to the left,  improve=1.2386730, (0 missing)
##       reimbursement2008 < 1735   to the left,  improve=1.2165300, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5300884, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4281976, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1607321, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1585   to the left,  agree=0.843, adj=0.1, (0 split)
## 
## Node number 6704: 88 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5454545  P(node) =0.0044
##     class counts:    36    40     6     5     1
##    probabilities: 0.409 0.455 0.068 0.057 0.011 
##   left son=13408 (55 obs) right son=13409 (33 obs)
##   Primary splits:
##       reimbursement2008 < 1925   to the left,  improve=0.8106061, (0 missing)
##       age               < 66.5   to the right, improve=0.6676136, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.6409091, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.6351931, (0 missing)
##       cancer            < 0.5    to the right, improve=0.5363636, (0 missing)
##   Surrogate splits:
##       alzheimers < 0.5    to the left,  agree=0.659, adj=0.091, (0 split)
##       age        < 72.5   to the left,  agree=0.648, adj=0.061, (0 split)
## 
## Node number 6705: 10 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0005
##     class counts:     5     2     0     3     0
##    probabilities: 0.500 0.200 0.000 0.300 0.000 
## 
## Node number 6708: 16 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0008
##     class counts:     5     8     3     0     0
##    probabilities: 0.312 0.500 0.188 0.000 0.000 
## 
## Node number 6709: 7 observations
##   predicted class=B1  expected loss=0.5714286  P(node) =0.00035
##     class counts:     3     1     3     0     0
##    probabilities: 0.429 0.143 0.429 0.000 0.000 
## 
## Node number 6850: 10 observations
##   predicted class=B1  expected loss=0.2  P(node) =0.0005
##     class counts:     8     0     1     1     0
##    probabilities: 0.800 0.000 0.100 0.100 0.000 
## 
## Node number 6851: 24 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.5  P(node) =0.0012
##     class counts:    12    10     1     1     0
##    probabilities: 0.500 0.417 0.042 0.042 0.000 
##   left son=13702 (14 obs) right son=13703 (10 obs)
##   Primary splits:
##       reimbursement2008 < 1775   to the left,  improve=2.23571400, (0 missing)
##       age               < 65.5   to the left,  improve=0.80714290, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.25000000, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.08333333, (0 missing)
##   Surrogate splits:
##       age          < 47     to the right, agree=0.667, adj=0.2, (0 split)
##       osteoporosis < 0.5    to the left,  agree=0.667, adj=0.2, (0 split)
## 
## Node number 6858: 22 observations
##   predicted class=B2  expected loss=0.5454545  P(node) =0.0011
##     class counts:     4    10     6     2     0
##    probabilities: 0.182 0.455 0.273 0.091 0.000 
## 
## Node number 6859: 7 observations
##   predicted class=B1  expected loss=0.5714286  P(node) =0.00035
##     class counts:     3     0     3     1     0
##    probabilities: 0.429 0.000 0.429 0.143 0.000 
## 
## Node number 6870: 46 observations,    complexity param=0.000253524
##   predicted class=B1  expected loss=0.5869565  P(node) =0.0023
##     class counts:    19    19     8     0     0
##    probabilities: 0.413 0.413 0.174 0.000 0.000 
##   left son=13740 (7 obs) right son=13741 (39 obs)
##   Primary splits:
##       copd              < 0.5    to the right, improve=2.2610290, (0 missing)
##       heart.failure     < 0.5    to the right, improve=2.1976590, (0 missing)
##       reimbursement2008 < 2225   to the left,  improve=1.5721340, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.1052510, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.7791149, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2110   to the left,  agree=0.87, adj=0.143, (0 split)
## 
## Node number 6871: 53 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4150943  P(node) =0.00265
##     class counts:    13    31     8     1     0
##    probabilities: 0.245 0.585 0.151 0.019 0.000 
##   left son=13742 (13 obs) right son=13743 (40 obs)
##   Primary splits:
##       reimbursement2008 < 1795   to the left,  improve=2.1412920, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.3502660, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.1700920, (0 missing)
##       age               < 75.5   to the right, improve=0.9132407, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.4028302, (0 missing)
##   Surrogate splits:
##       age  < 81.5   to the right, agree=0.792, adj=0.154, (0 split)
##       copd < 0.5    to the right, agree=0.792, adj=0.154, (0 split)
## 
## Node number 6934: 41 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5609756  P(node) =0.00205
##     class counts:    18    17     6     0     0
##    probabilities: 0.439 0.415 0.146 0.000 0.000 
##   left son=13868 (30 obs) right son=13869 (11 obs)
##   Primary splits:
##       reimbursement2008 < 2680   to the right, improve=1.4919440, (0 missing)
##       age               < 74.5   to the left,  improve=0.6876399, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.4137873, (0 missing)
##       depression        < 0.5    to the left,  improve=0.2054539, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1305018, (0 missing)
## 
## Node number 6935: 14 observations
##   predicted class=B1  expected loss=0.3571429  P(node) =0.0007
##     class counts:     9     0     2     3     0
##    probabilities: 0.643 0.000 0.143 0.214 0.000 
## 
## Node number 6936: 7 observations
##   predicted class=B1  expected loss=0  P(node) =0.00035
##     class counts:     7     0     0     0     0
##    probabilities: 1.000 0.000 0.000 0.000 0.000 
## 
## Node number 6937: 51 observations,    complexity param=0.0001014096
##   predicted class=B1  expected loss=0.4901961  P(node) =0.00255
##     class counts:    26    11    10     2     2
##    probabilities: 0.510 0.216 0.196 0.039 0.039 
##   left son=13874 (24 obs) right son=13875 (27 obs)
##   Primary splits:
##       reimbursement2008 < 2865   to the left,  improve=1.0511980, (0 missing)
##       age               < 70.5   to the right, improve=0.8104575, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.4304506, (0 missing)
##       kidney            < 0.5    to the right, improve=0.2867201, (0 missing)
##       depression        < 0.5    to the right, improve=0.2437908, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.902, adj=0.792, (0 split)
##       age        < 71.5   to the left,  agree=0.627, adj=0.208, (0 split)
##       kidney     < 0.5    to the right, agree=0.627, adj=0.208, (0 split)
##       copd       < 0.5    to the left,  agree=0.569, adj=0.083, (0 split)
##       depression < 0.5    to the right, agree=0.549, adj=0.042, (0 split)
## 
## Node number 6938: 33 observations,    complexity param=0.0002662002
##   predicted class=B2  expected loss=0.5454545  P(node) =0.00165
##     class counts:    13    15     4     1     0
##    probabilities: 0.394 0.455 0.121 0.030 0.000 
##   left son=13876 (7 obs) right son=13877 (26 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=0.8421578, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7121212, (0 missing)
##       reimbursement2008 < 2665   to the left,  improve=0.5454545, (0 missing)
##       age               < 82.5   to the left,  improve=0.5454545, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.3787879, (0 missing)
## 
## Node number 6939: 13 observations
##   predicted class=B3  expected loss=0.6153846  P(node) =0.00065
##     class counts:     4     3     5     1     0
##    probabilities: 0.308 0.231 0.385 0.077 0.000 
## 
## Node number 6980: 23 observations
##   predicted class=B1  expected loss=0.3478261  P(node) =0.00115
##     class counts:    15     2     3     3     0
##    probabilities: 0.652 0.087 0.130 0.130 0.000 
## 
## Node number 6981: 44 observations,    complexity param=0.000253524
##   predicted class=B1  expected loss=0.5227273  P(node) =0.0022
##     class counts:    21    16     3     4     0
##    probabilities: 0.477 0.364 0.068 0.091 0.000 
##   left son=13962 (23 obs) right son=13963 (21 obs)
##   Primary splits:
##       reimbursement2008 < 2715   to the left,  improve=0.8579898, (0 missing)
##       depression        < 0.5    to the right, improve=0.8196673, (0 missing)
##       age               < 66.5   to the right, improve=0.5631313, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3181818, (0 missing)
##       copd              < 0.5    to the right, improve=0.1969697, (0 missing)
##   Surrogate splits:
##       age        < 66.5   to the right, agree=0.614, adj=0.190, (0 split)
##       depression < 0.5    to the right, agree=0.545, adj=0.048, (0 split)
## 
## Node number 6982: 13 observations
##   predicted class=B1  expected loss=0.3846154  P(node) =0.00065
##     class counts:     8     4     1     0     0
##    probabilities: 0.615 0.308 0.077 0.000 0.000 
## 
## Node number 6983: 45 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.4444444  P(node) =0.00225
##     class counts:    12    25     4     4     0
##    probabilities: 0.267 0.556 0.089 0.089 0.000 
##   left son=13966 (10 obs) right son=13967 (35 obs)
##   Primary splits:
##       reimbursement2008 < 3285   to the right, improve=1.5428570, (0 missing)
##       depression        < 0.5    to the left,  improve=1.2040490, (0 missing)
##       age               < 71     to the right, improve=1.0175680, (0 missing)
##       copd              < 0.5    to the left,  improve=0.9777778, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.3105769, (0 missing)
## 
## Node number 7004: 19 observations
##   predicted class=B2  expected loss=0.5263158  P(node) =0.00095
##     class counts:     4     9     4     2     0
##    probabilities: 0.211 0.474 0.211 0.105 0.000 
## 
## Node number 7005: 20 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.6  P(node) =0.001
##     class counts:     8     3     5     4     0
##    probabilities: 0.400 0.150 0.250 0.200 0.000 
##   left son=14010 (8 obs) right son=14011 (12 obs)
##   Primary splits:
##       reimbursement2008 < 2955   to the left,  improve=1.5500000, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=0.7166667, (0 missing)
##       age               < 79     to the left,  improve=0.4010101, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.80, adj=0.500, (0 split)
##       age        < 58.5   to the left,  agree=0.70, adj=0.250, (0 split)
##       cancer     < 0.5    to the right, agree=0.65, adj=0.125, (0 split)
## 
## Node number 7040: 32 observations,    complexity param=0.0002788764
##   predicted class=B1  expected loss=0.46875  P(node) =0.0016
##     class counts:    17    11     4     0     0
##    probabilities: 0.531 0.344 0.125 0.000 0.000 
##   left son=14080 (18 obs) right son=14081 (14 obs)
##   Primary splits:
##       depression   < 0.5    to the left,  improve=1.3700400, (0 missing)
##       copd         < 0.5    to the left,  improve=1.1875000, (0 missing)
##       diabetes     < 0.5    to the right, improve=0.7541667, (0 missing)
##       osteoporosis < 0.5    to the left,  improve=0.4875000, (0 missing)
##       age          < 68.5   to the left,  improve=0.4494048, (0 missing)
##   Surrogate splits:
##       copd              < 0.5    to the left,  agree=0.688, adj=0.286, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.688, adj=0.286, (0 split)
##       age               < 37.5   to the right, agree=0.625, adj=0.143, (0 split)
##       reimbursement2008 < 2915   to the left,  agree=0.625, adj=0.143, (0 split)
## 
## Node number 7041: 8 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0004
##     class counts:     1     4     1     1     1
##    probabilities: 0.125 0.500 0.125 0.125 0.125 
## 
## Node number 7042: 52 observations
##   predicted class=B2  expected loss=0.4423077  P(node) =0.0026
##     class counts:    15    29     7     1     0
##    probabilities: 0.288 0.558 0.135 0.019 0.000 
## 
## Node number 7043: 12 observations
##   predicted class=B1  expected loss=0.5833333  P(node) =0.0006
##     class counts:     5     3     2     2     0
##    probabilities: 0.417 0.250 0.167 0.167 0.000 
## 
## Node number 7046: 19 observations
##   predicted class=B2  expected loss=0.6315789  P(node) =0.00095
##     class counts:     6     7     6     0     0
##    probabilities: 0.316 0.368 0.316 0.000 0.000 
## 
## Node number 7047: 7 observations
##   predicted class=B3  expected loss=0.1428571  P(node) =0.00035
##     class counts:     1     0     6     0     0
##    probabilities: 0.143 0.000 0.857 0.000 0.000 
## 
## Node number 7194: 79 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4177215  P(node) =0.00395
##     class counts:    46    17    15     1     0
##    probabilities: 0.582 0.215 0.190 0.013 0.000 
##   left son=14388 (32 obs) right son=14389 (47 obs)
##   Primary splits:
##       reimbursement2008 < 4235   to the left,  improve=1.8012560, (0 missing)
##       age               < 70.5   to the right, improve=1.0692790, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.6128692, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4137464, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.3172132, (0 missing)
##   Surrogate splits:
##       age < 76.5   to the right, agree=0.646, adj=0.125, (0 split)
## 
## Node number 7195: 18 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0009
##     class counts:     6     9     2     1     0
##    probabilities: 0.333 0.500 0.111 0.056 0.000 
## 
## Node number 7502: 10 observations
##   predicted class=B1  expected loss=0.6  P(node) =0.0005
##     class counts:     4     3     2     1     0
##    probabilities: 0.400 0.300 0.200 0.100 0.000 
## 
## Node number 7503: 15 observations
##   predicted class=B2  expected loss=0.3333333  P(node) =0.00075
##     class counts:     2    10     2     1     0
##    probabilities: 0.133 0.667 0.133 0.067 0.000 
## 
## Node number 7516: 18 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.0009
##     class counts:     4    10     3     1     0
##    probabilities: 0.222 0.556 0.167 0.056 0.000 
## 
## Node number 7517: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     1     2     3     1     0
##    probabilities: 0.143 0.286 0.429 0.143 0.000 
## 
## Node number 7682: 7 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.00035
##     class counts:     4     3     0     0     0
##    probabilities: 0.571 0.429 0.000 0.000 0.000 
## 
## Node number 7683: 17 observations
##   predicted class=B2  expected loss=0.4117647  P(node) =0.00085
##     class counts:     6    10     1     0     0
##    probabilities: 0.353 0.588 0.059 0.000 0.000 
## 
## Node number 7686: 76 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4868421  P(node) =0.0038
##     class counts:    39    17    18     2     0
##    probabilities: 0.513 0.224 0.237 0.026 0.000 
##   left son=15372 (20 obs) right son=15373 (56 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=1.6184210, (0 missing)
##       reimbursement2008 < 3755   to the left,  improve=1.0173570, (0 missing)
##       age               < 45.5   to the left,  improve=0.4522720, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4366029, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.4050802, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 3515   to the left,  agree=0.763, adj=0.1, (0 split)
## 
## Node number 7687: 28 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0014
##     class counts:     8    14     5     1     0
##    probabilities: 0.286 0.500 0.179 0.036 0.000 
## 
## Node number 7698: 9 observations
##   predicted class=B1  expected loss=0.5555556  P(node) =0.00045
##     class counts:     4     2     0     2     1
##    probabilities: 0.444 0.222 0.000 0.222 0.111 
## 
## Node number 7699: 15 observations
##   predicted class=B2  expected loss=0.4666667  P(node) =0.00075
##     class counts:     2     8     2     3     0
##    probabilities: 0.133 0.533 0.133 0.200 0.000 
## 
## Node number 7712: 11 observations
##   predicted class=B1  expected loss=0.2727273  P(node) =0.00055
##     class counts:     8     0     2     1     0
##    probabilities: 0.727 0.000 0.182 0.091 0.000 
## 
## Node number 7713: 106 observations,    complexity param=0.0003295812
##   predicted class=B1  expected loss=0.5  P(node) =0.0053
##     class counts:    53    35    11     7     0
##    probabilities: 0.500 0.330 0.104 0.066 0.000 
##   left son=15426 (85 obs) right son=15427 (21 obs)
##   Primary splits:
##       reimbursement2008 < 6040   to the right, improve=2.0740760, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.1004920, (0 missing)
##       age               < 83.5   to the left,  improve=0.9104868, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4595413, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.4547943, (0 missing)
## 
## Node number 7714: 13 observations
##   predicted class=B1  expected loss=0.4615385  P(node) =0.00065
##     class counts:     7     5     1     0     0
##    probabilities: 0.538 0.385 0.077 0.000 0.000 
## 
## Node number 7715: 14 observations
##   predicted class=B2  expected loss=0.3571429  P(node) =0.0007
##     class counts:     3     9     1     1     0
##    probabilities: 0.214 0.643 0.071 0.071 0.000 
## 
## Node number 7724: 14 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0007
##     class counts:     7     4     3     0     0
##    probabilities: 0.500 0.286 0.214 0.000 0.000 
## 
## Node number 7725: 47 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.3404255  P(node) =0.00235
##     class counts:     7    31     7     2     0
##    probabilities: 0.149 0.660 0.149 0.043 0.000 
##   left son=15450 (26 obs) right son=15451 (21 obs)
##   Primary splits:
##       age               < 81.5   to the left,  improve=1.7492790, (0 missing)
##       copd              < 0.5    to the left,  improve=1.4122830, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.0571870, (0 missing)
##       reimbursement2008 < 6790   to the right, improve=0.9666891, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.4557060, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 6495   to the right, agree=0.596, adj=0.095, (0 split)
##       copd              < 0.5    to the left,  agree=0.574, adj=0.048, (0 split)
## 
## Node number 7726: 49 observations,    complexity param=0.0004056384
##   predicted class=B2  expected loss=0.6122449  P(node) =0.00245
##     class counts:    15    19     7     7     1
##    probabilities: 0.306 0.388 0.143 0.143 0.020 
##   left son=15452 (38 obs) right son=15453 (11 obs)
##   Primary splits:
##       stroke            < 0.5    to the left,  improve=1.7955280, (0 missing)
##       copd              < 0.5    to the left,  improve=1.3997190, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.3583390, (0 missing)
##       reimbursement2008 < 32725  to the left,  improve=1.0680270, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6528868, (0 missing)
## 
## Node number 7727: 19 observations
##   predicted class=B3  expected loss=0.5263158  P(node) =0.00095
##     class counts:     5     4     9     1     0
##    probabilities: 0.263 0.211 0.474 0.053 0.000 
## 
## Node number 7740: 17 observations
##   predicted class=B1  expected loss=0.4705882  P(node) =0.00085
##     class counts:     9     5     2     1     0
##    probabilities: 0.529 0.294 0.118 0.059 0.000 
## 
## Node number 7741: 20 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.55  P(node) =0.001
##     class counts:     5     9     4     2     0
##    probabilities: 0.250 0.450 0.200 0.100 0.000 
##   left son=15482 (7 obs) right son=15483 (13 obs)
##   Primary splits:
##       age               < 86.5   to the right, improve=0.9747253, (0 missing)
##       reimbursement2008 < 4655   to the right, improve=0.9000000, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8208791, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.3666667, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2274725, (0 missing)
##   Surrogate splits:
##       osteoporosis      < 0.5    to the right, agree=0.8, adj=0.429, (0 split)
##       stroke            < 0.5    to the right, agree=0.7, adj=0.143, (0 split)
##       reimbursement2008 < 4145   to the left,  agree=0.7, adj=0.143, (0 split)
## 
## Node number 7786: 11 observations
##   predicted class=B1  expected loss=0.4545455  P(node) =0.00055
##     class counts:     6     2     3     0     0
##    probabilities: 0.545 0.182 0.273 0.000 0.000 
## 
## Node number 7787: 22 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.5  P(node) =0.0011
##     class counts:     2     7    11     2     0
##    probabilities: 0.091 0.318 0.500 0.091 0.000 
##   left son=15574 (8 obs) right son=15575 (14 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=1.23051900, (0 missing)
##       age               < 67.5   to the left,  improve=1.14242400, (0 missing)
##       reimbursement2008 < 9135   to the left,  improve=0.44242420, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.29004330, (0 missing)
##       depression        < 0.5    to the left,  improve=0.08766234, (0 missing)
##   Surrogate splits:
##       age               < 70.5   to the right, agree=0.727, adj=0.25, (0 split)
##       reimbursement2008 < 6475   to the left,  agree=0.727, adj=0.25, (0 split)
## 
## Node number 7788: 26 observations,    complexity param=7.60572e-05
##   predicted class=B2  expected loss=0.6538462  P(node) =0.0013
##     class counts:     6     9     9     2     0
##    probabilities: 0.231 0.346 0.346 0.077 0.000 
##   left son=15576 (16 obs) right son=15577 (10 obs)
##   Primary splits:
##       age               < 76.5   to the right, improve=0.60576920, (0 missing)
##       reimbursement2008 < 5835   to the left,  improve=0.21769730, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.07692308, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.06107226, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4000   to the right, agree=0.654, adj=0.1, (0 split)
## 
## Node number 7789: 7 observations
##   predicted class=B3  expected loss=0.2857143  P(node) =0.00035
##     class counts:     1     0     5     1     0
##    probabilities: 0.143 0.000 0.714 0.143 0.000 
## 
## Node number 7790: 13 observations
##   predicted class=B2  expected loss=0.1538462  P(node) =0.00065
##     class counts:     0    11     1     1     0
##    probabilities: 0.000 0.846 0.077 0.077 0.000 
## 
## Node number 7791: 17 observations
##   predicted class=B3  expected loss=0.5882353  P(node) =0.00085
##     class counts:     1     6     7     3     0
##    probabilities: 0.059 0.353 0.412 0.176 0.000 
## 
## Node number 7880: 7 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.00035
##     class counts:     5     1     1     0     0
##    probabilities: 0.714 0.143 0.143 0.000 0.000 
## 
## Node number 7881: 52 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.4423077  P(node) =0.0026
##     class counts:    14    29     5     3     1
##    probabilities: 0.269 0.558 0.096 0.058 0.019 
##   left son=15762 (32 obs) right son=15763 (20 obs)
##   Primary splits:
##       reimbursement2008 < 4955   to the right, improve=2.1471150, (0 missing)
##       age               < 74.5   to the right, improve=1.8974360, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.3934850, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7370875, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6891199, (0 missing)
##   Surrogate splits:
##       age < 76.5   to the left,  agree=0.75, adj=0.35, (0 split)
## 
## Node number 7882: 18 observations
##   predicted class=B1  expected loss=0.5555556  P(node) =0.0009
##     class counts:     8     5     3     2     0
##    probabilities: 0.444 0.278 0.167 0.111 0.000 
## 
## Node number 7883: 8 observations
##   predicted class=B2  expected loss=0.625  P(node) =0.0004
##     class counts:     0     3     2     3     0
##    probabilities: 0.000 0.375 0.250 0.375 0.000 
## 
## Node number 7902: 15 observations
##   predicted class=B2  expected loss=0.5333333  P(node) =0.00075
##     class counts:     3     7     5     0     0
##    probabilities: 0.200 0.467 0.333 0.000 0.000 
## 
## Node number 7903: 7 observations
##   predicted class=B3  expected loss=0.1428571  P(node) =0.00035
##     class counts:     0     1     6     0     0
##    probabilities: 0.000 0.143 0.857 0.000 0.000 
## 
## Node number 7912: 30 observations
##   predicted class=B2  expected loss=0.2666667  P(node) =0.0015
##     class counts:     3    22     2     3     0
##    probabilities: 0.100 0.733 0.067 0.100 0.000 
## 
## Node number 7913: 22 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.6363636  P(node) =0.0011
##     class counts:     5     8     8     1     0
##    probabilities: 0.227 0.364 0.364 0.045 0.000 
##   left son=15826 (12 obs) right son=15827 (10 obs)
##   Primary splits:
##       age               < 72.5   to the right, improve=1.7666670, (0 missing)
##       reimbursement2008 < 35585  to the left,  improve=1.1142860, (0 missing)
##       copd              < 0.5    to the right, improve=0.2500000, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.1452991, (0 missing)
##       cancer            < 0.5    to the right, improve=0.1452991, (0 missing)
##   Surrogate splits:
##       copd              < 0.5    to the right, agree=0.636, adj=0.2, (0 split)
##       stroke            < 0.5    to the left,  agree=0.636, adj=0.2, (0 split)
##       reimbursement2008 < 28350  to the left,  agree=0.636, adj=0.2, (0 split)
##       cancer            < 0.5    to the right, agree=0.591, adj=0.1, (0 split)
## 
## Node number 7914: 90 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5222222  P(node) =0.0045
##     class counts:    18    43    20     8     1
##    probabilities: 0.200 0.478 0.222 0.089 0.011 
##   left son=15828 (53 obs) right son=15829 (37 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=1.6669610, (0 missing)
##       reimbursement2008 < 7520   to the left,  improve=1.6335890, (0 missing)
##       age               < 72.5   to the right, improve=1.6301840, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.1552350, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.9296296, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 6155   to the left,  agree=0.644, adj=0.135, (0 split)
##       age               < 70.5   to the right, agree=0.633, adj=0.108, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.611, adj=0.054, (0 split)
##       copd              < 0.5    to the left,  agree=0.600, adj=0.027, (0 split)
## 
## Node number 7915: 74 observations,    complexity param=0.0002281716
##   predicted class=B3  expected loss=0.6486486  P(node) =0.0037
##     class counts:    16    25    26     6     1
##    probabilities: 0.216 0.338 0.351 0.081 0.014 
##   left son=15830 (46 obs) right son=15831 (28 obs)
##   Primary splits:
##       age               < 79.5   to the left,  improve=1.5743660, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.1621620, (0 missing)
##       reimbursement2008 < 10440  to the left,  improve=0.7888245, (0 missing)
##       copd              < 0.5    to the left,  improve=0.7705706, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.6708416, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4315   to the right, agree=0.662, adj=0.107, (0 split)
## 
## Node number 7938: 24 observations,    complexity param=0.0002028192
##   predicted class=B3  expected loss=0.625  P(node) =0.0012
##     class counts:     7     8     9     0     0
##    probabilities: 0.292 0.333 0.375 0.000 0.000 
##   left son=15876 (13 obs) right son=15877 (11 obs)
##   Primary splits:
##       reimbursement2008 < 13055  to the right, improve=1.2453380, (0 missing)
##       copd              < 0.5    to the right, improve=0.7166667, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5833333, (0 missing)
##       age               < 90.5   to the right, improve=0.2864146, (0 missing)
##       stroke            < 0.5    to the right, improve=0.2864146, (0 missing)
##   Surrogate splits:
##       copd          < 0.5    to the right, agree=0.667, adj=0.273, (0 split)
##       age           < 93.5   to the left,  agree=0.625, adj=0.182, (0 split)
##       depression    < 0.5    to the left,  agree=0.625, adj=0.182, (0 split)
##       heart.failure < 0.5    to the right, agree=0.583, adj=0.091, (0 split)
##       stroke        < 0.5    to the right, agree=0.583, adj=0.091, (0 split)
## 
## Node number 7939: 8 observations
##   predicted class=B1  expected loss=0.625  P(node) =0.0004
##     class counts:     3     1     0     2     2
##    probabilities: 0.375 0.125 0.000 0.250 0.250 
## 
## Node number 7948: 169 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.591716  P(node) =0.00845
##     class counts:    43    69    21    31     5
##    probabilities: 0.254 0.408 0.124 0.183 0.030 
##   left son=15896 (24 obs) right son=15897 (145 obs)
##   Primary splits:
##       age               < 75.5   to the right, improve=2.0759710, (0 missing)
##       stroke            < 0.5    to the right, improve=1.4276950, (0 missing)
##       reimbursement2008 < 10940  to the left,  improve=0.9442655, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7626810, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4382567, (0 missing)
## 
## Node number 7949: 8 observations
##   predicted class=B3  expected loss=0.5  P(node) =0.0004
##     class counts:     3     0     4     1     0
##    probabilities: 0.375 0.000 0.500 0.125 0.000 
## 
## Node number 7950: 34 observations,    complexity param=0.0004563432
##   predicted class=B3  expected loss=0.6764706  P(node) =0.0017
##     class counts:     9     8    11     4     2
##    probabilities: 0.265 0.235 0.324 0.118 0.059 
##   left son=15900 (10 obs) right son=15901 (24 obs)
##   Primary splits:
##       copd              < 0.5    to the right, improve=1.4882350, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.2805430, (0 missing)
##       reimbursement2008 < 7950   to the right, improve=0.9321506, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.9321506, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5215686, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 13335  to the right, agree=0.765, adj=0.2, (0 split)
## 
## Node number 7951: 57 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.5789474  P(node) =0.00285
##     class counts:     5    24    13    14     1
##    probabilities: 0.088 0.421 0.228 0.246 0.018 
##   left son=15902 (38 obs) right son=15903 (19 obs)
##   Primary splits:
##       reimbursement2008 < 9695   to the right, improve=2.9298250, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.2396330, (0 missing)
##       depression        < 0.5    to the right, improve=1.0943470, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.9573099, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.9534551, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.807, adj=0.421, (0 split)
##       age        < 78.5   to the right, agree=0.702, adj=0.105, (0 split)
## 
## Node number 7960: 48 observations,    complexity param=0.0003650745
##   predicted class=B2  expected loss=0.4791667  P(node) =0.0024
##     class counts:     9    25     7     6     1
##    probabilities: 0.188 0.521 0.146 0.125 0.021 
##   left son=15920 (25 obs) right son=15921 (23 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=1.7330430, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.2714290, (0 missing)
##       age               < 82.5   to the left,  improve=0.9889435, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8949580, (0 missing)
##       reimbursement2008 < 5780   to the right, improve=0.7500000, (0 missing)
##   Surrogate splits:
##       age               < 82.5   to the right, agree=0.625, adj=0.217, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.604, adj=0.174, (0 split)
##       reimbursement2008 < 4785   to the right, agree=0.604, adj=0.174, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.562, adj=0.087, (0 split)
##       ihd               < 0.5    to the left,  agree=0.562, adj=0.087, (0 split)
## 
## Node number 7961: 162 observations,    complexity param=0.0003650745
##   predicted class=B2  expected loss=0.6419753  P(node) =0.0081
##     class counts:    35    58    40    25     4
##    probabilities: 0.216 0.358 0.247 0.154 0.025 
##   left son=15922 (94 obs) right son=15923 (68 obs)
##   Primary splits:
##       reimbursement2008 < 4895   to the left,  improve=2.1304950, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.6052440, (0 missing)
##       ihd               < 0.5    to the right, improve=1.1317140, (0 missing)
##       age               < 59.5   to the left,  improve=0.9109347, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.8391381, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.623, adj=0.103, (0 split)
##       copd   < 0.5    to the left,  agree=0.599, adj=0.044, (0 split)
##       stroke < 0.5    to the left,  agree=0.586, adj=0.015, (0 split)
## 
## Node number 7962: 17 observations
##   predicted class=B2  expected loss=0.4705882  P(node) =0.00085
##     class counts:     0     9     7     0     1
##    probabilities: 0.000 0.529 0.412 0.000 0.059 
## 
## Node number 7963: 8 observations
##   predicted class=B3  expected loss=0.375  P(node) =0.0004
##     class counts:     1     1     5     1     0
##    probabilities: 0.125 0.125 0.625 0.125 0.000 
## 
## Node number 8018: 29 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.5172414  P(node) =0.00145
##     class counts:    10    14     3     2     0
##    probabilities: 0.345 0.483 0.103 0.069 0.000 
##   left son=16036 (22 obs) right son=16037 (7 obs)
##   Primary splits:
##       reimbursement2008 < 4270   to the left,  improve=1.4746980, (0 missing)
##       age               < 64.5   to the right, improve=0.8383341, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6291413, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4761407, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.3805419, (0 missing)
## 
## Node number 8019: 40 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.45  P(node) =0.002
##     class counts:     4    22    10     3     1
##    probabilities: 0.100 0.550 0.250 0.075 0.025 
##   left son=16038 (31 obs) right son=16039 (9 obs)
##   Primary splits:
##       reimbursement2008 < 3995   to the right, improve=2.3557350, (0 missing)
##       age               < 81.5   to the right, improve=0.8598901, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6281362, (0 missing)
##       depression        < 0.5    to the right, improve=0.4033333, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.2700000, (0 missing)
## 
## Node number 8052: 35 observations
##   predicted class=B2  expected loss=0.6  P(node) =0.00175
##     class counts:     7    14     7     6     1
##    probabilities: 0.200 0.400 0.200 0.171 0.029 
## 
## Node number 8053: 152 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5197368  P(node) =0.0076
##     class counts:    13    73    46    16     4
##    probabilities: 0.086 0.480 0.303 0.105 0.026 
##   left son=16106 (130 obs) right son=16107 (22 obs)
##   Primary splits:
##       reimbursement2008 < 13595  to the left,  improve=1.2442950, (0 missing)
##       age               < 95.5   to the right, improve=0.7711988, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.6892208, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.3316563, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.2600877, (0 missing)
## 
## Node number 8128: 10 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0005
##     class counts:     4     5     1     0     0
##    probabilities: 0.400 0.500 0.100 0.000 0.000 
## 
## Node number 8129: 49 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.6734694  P(node) =0.00245
##     class counts:    16     7    11    15     0
##    probabilities: 0.327 0.143 0.224 0.306 0.000 
##   left son=16258 (41 obs) right son=16259 (8 obs)
##   Primary splits:
##       age               < 86.5   to the left,  improve=1.5618470, (0 missing)
##       depression        < 0.5    to the right, improve=1.5156330, (0 missing)
##       cancer            < 0.5    to the right, improve=1.3809520, (0 missing)
##       reimbursement2008 < 19645  to the right, improve=0.8857143, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.6959034, (0 missing)
## 
## Node number 8136: 7 observations
##   predicted class=B1  expected loss=0.5714286  P(node) =0.00035
##     class counts:     3     1     1     2     0
##    probabilities: 0.429 0.143 0.143 0.286 0.000 
## 
## Node number 8137: 25 observations
##   predicted class=B2  expected loss=0.28  P(node) =0.00125
##     class counts:     1    18     3     1     2
##    probabilities: 0.040 0.720 0.120 0.040 0.080 
## 
## Node number 8140: 35 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5142857  P(node) =0.00175
##     class counts:     5    17     6     5     2
##    probabilities: 0.143 0.486 0.171 0.143 0.057 
##   left son=16280 (28 obs) right son=16281 (7 obs)
##   Primary splits:
##       age               < 60     to the right, improve=2.0285710, (0 missing)
##       reimbursement2008 < 20455  to the left,  improve=1.0914290, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9064713, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5840160, (0 missing)
##       stroke            < 0.5    to the right, improve=0.5047619, (0 missing)
## 
## Node number 8141: 46 observations,    complexity param=0.000380286
##   predicted class=B4  expected loss=0.7173913  P(node) =0.0023
##     class counts:     9    11    12    13     1
##    probabilities: 0.196 0.239 0.261 0.283 0.022 
##   left son=16282 (39 obs) right son=16283 (7 obs)
##   Primary splits:
##       age               < 75.5   to the right, improve=1.7130120, (0 missing)
##       reimbursement2008 < 17795  to the right, improve=1.6235180, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.6115561, (0 missing)
##       bucket2008        < 3.5    to the right, improve=0.3603865, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.2409420, (0 missing)
## 
## Node number 8144: 29 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4482759  P(node) =0.00145
##     class counts:     3    16     9     0     1
##    probabilities: 0.103 0.552 0.310 0.000 0.034 
##   left son=16288 (22 obs) right son=16289 (7 obs)
##   Primary splits:
##       age               < 86     to the left,  improve=0.9046126, (0 missing)
##       reimbursement2008 < 24075  to the left,  improve=0.8900383, (0 missing)
##       cancer            < 0.5    to the right, improve=0.6344828, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5056366, (0 missing)
##       depression        < 0.5    to the right, improve=0.4789272, (0 missing)
## 
## Node number 8145: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     1     1     4     0     1
##    probabilities: 0.143 0.143 0.571 0.000 0.143 
## 
## Node number 8146: 55 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.6  P(node) =0.00275
##     class counts:    13    22     9     9     2
##    probabilities: 0.236 0.400 0.164 0.164 0.036 
##   left son=16292 (20 obs) right son=16293 (35 obs)
##   Primary splits:
##       reimbursement2008 < 18970  to the left,  improve=2.780519, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=2.780519, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.478839, (0 missing)
##       depression        < 0.5    to the left,  improve=1.215758, (0 missing)
##       age               < 83.5   to the right, improve=1.152951, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the left,  agree=1.000, adj=1.00, (0 split)
##       age        < 87     to the right, agree=0.655, adj=0.05, (0 split)
## 
## Node number 8147: 34 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5588235  P(node) =0.0017
##     class counts:     0    15    10     7     2
##    probabilities: 0.000 0.441 0.294 0.206 0.059 
##   left son=16294 (9 obs) right son=16295 (25 obs)
##   Primary splits:
##       age               < 77     to the left,  improve=2.0112420, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.1167850, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.0156860, (0 missing)
##       reimbursement2008 < 16720  to the right, improve=0.6577915, (0 missing)
##       depression        < 0.5    to the left,  improve=0.1471751, (0 missing)
## 
## Node number 8182: 17 observations
##   predicted class=B2  expected loss=0.4705882  P(node) =0.00085
##     class counts:     0     9     1     7     0
##    probabilities: 0.000 0.529 0.059 0.412 0.000 
## 
## Node number 8183: 16 observations
##   predicted class=B4  expected loss=0.5625  P(node) =0.0008
##     class counts:     2     3     4     7     0
##    probabilities: 0.125 0.188 0.250 0.438 0.000 
## 
## Node number 8184: 13 observations
##   predicted class=B1  expected loss=0.5384615  P(node) =0.00065
##     class counts:     6     2     2     2     1
##    probabilities: 0.462 0.154 0.154 0.154 0.077 
## 
## Node number 8185: 13 observations
##   predicted class=B2  expected loss=0.4615385  P(node) =0.00065
##     class counts:     0     7     3     3     0
##    probabilities: 0.000 0.538 0.231 0.231 0.000 
## 
## Node number 8186: 13 observations
##   predicted class=B2  expected loss=0.5384615  P(node) =0.00065
##     class counts:     0     6     5     1     1
##    probabilities: 0.000 0.462 0.385 0.077 0.077 
## 
## Node number 8187: 58 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5862069  P(node) =0.0029
##     class counts:     0    24     7    22     5
##    probabilities: 0.000 0.414 0.121 0.379 0.086 
##   left son=16374 (39 obs) right son=16375 (19 obs)
##   Primary splits:
##       age               < 79.5   to the left,  improve=2.1351850, (0 missing)
##       cancer            < 0.5    to the right, improve=1.3166520, (0 missing)
##       reimbursement2008 < 72235  to the left,  improve=1.1115240, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.7016920, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6656672, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 83625  to the left,  agree=0.724, adj=0.158, (0 split)
##       cancer            < 0.5    to the left,  agree=0.690, adj=0.053, (0 split)
## 
## Node number 8188: 150 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6733333  P(node) =0.0075
##     class counts:    14    49    42    38     7
##    probabilities: 0.093 0.327 0.280 0.253 0.047 
##   left son=16376 (139 obs) right son=16377 (11 obs)
##   Primary splits:
##       reimbursement2008 < 88685  to the left,  improve=1.8771920, (0 missing)
##       age               < 57.5   to the right, improve=1.3581570, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.0064300, (0 missing)
##       bucket2008        < 4.5    to the right, improve=0.9466667, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8913369, (0 missing)
## 
## Node number 8189: 30 observations,    complexity param=0.0003042288
##   predicted class=B4  expected loss=0.5666667  P(node) =0.0015
##     class counts:     0     5    11    13     1
##    probabilities: 0.000 0.167 0.367 0.433 0.033 
##   left son=16378 (9 obs) right son=16379 (21 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=0.7682540, (0 missing)
##       reimbursement2008 < 58390  to the right, improve=0.5971014, (0 missing)
##       depression        < 0.5    to the right, improve=0.5777778, (0 missing)
##       age               < 85.5   to the left,  improve=0.3948963, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2492754, (0 missing)
##   Surrogate splits:
##       age < 87.5   to the right, agree=0.733, adj=0.111, (0 split)
## 
## Node number 8190: 39 observations,    complexity param=0.0001521144
##   predicted class=B4  expected loss=0.6410256  P(node) =0.00195
##     class counts:     4    10     8    14     3
##    probabilities: 0.103 0.256 0.205 0.359 0.077 
##   left son=16380 (27 obs) right son=16381 (12 obs)
##   Primary splits:
##       depression   < 0.5    to the right, improve=1.4245010, (0 missing)
##       age          < 71.5   to the right, improve=1.2051280, (0 missing)
##       osteoporosis < 0.5    to the left,  improve=1.0439950, (0 missing)
##       copd         < 0.5    to the left,  improve=0.8689459, (0 missing)
##       cancer       < 0.5    to the left,  improve=0.6652422, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 35330  to the left,  agree=0.744, adj=0.167, (0 split)
## 
## Node number 8191: 15 observations
##   predicted class=B4  expected loss=0.2  P(node) =0.00075
##     class counts:     0     1     2    12     0
##    probabilities: 0.000 0.067 0.133 0.800 0.000 
## 
## Node number 10284: 321 observations
##   predicted class=B1  expected loss=0.1619938  P(node) =0.01605
##     class counts:   269    28    19     3     2
##    probabilities: 0.838 0.087 0.059 0.009 0.006 
## 
## Node number 10285: 77 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2337662  P(node) =0.00385
##     class counts:    59    11     7     0     0
##    probabilities: 0.766 0.143 0.091 0.000 0.000 
##   left son=20570 (70 obs) right son=20571 (7 obs)
##   Primary splits:
##       age               < 86.5   to the left,  improve=4.6987010, (0 missing)
##       depression        < 0.5    to the left,  improve=1.7558440, (0 missing)
##       reimbursement2008 < 385    to the left,  improve=0.6180762, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.1356976, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1272727, (0 missing)
## 
## Node number 10286: 10 observations
##   predicted class=B1  expected loss=0.1  P(node) =0.0005
##     class counts:     9     1     0     0     0
##    probabilities: 0.900 0.100 0.000 0.000 0.000 
## 
## Node number 10287: 22 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3636364  P(node) =0.0011
##     class counts:    14     7     0     1     0
##    probabilities: 0.636 0.318 0.000 0.045 0.000 
##   left son=20574 (14 obs) right son=20575 (8 obs)
##   Primary splits:
##       age               < 78.5   to the left,  improve=3.13961000, (0 missing)
##       reimbursement2008 < 485    to the right, improve=0.08484848, (0 missing)
##   Surrogate splits:
##       depression < 0.5    to the left,  agree=0.727, adj=0.25, (0 split)
## 
## Node number 11538: 23 observations
##   predicted class=B1  expected loss=0.3478261  P(node) =0.00115
##     class counts:    15     5     3     0     0
##    probabilities: 0.652 0.217 0.130 0.000 0.000 
## 
## Node number 11539: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     2     5     0     0     0
##    probabilities: 0.286 0.714 0.000 0.000 0.000 
## 
## Node number 11798: 8 observations
##   predicted class=B1  expected loss=0.125  P(node) =0.0004
##     class counts:     7     0     1     0     0
##    probabilities: 0.875 0.000 0.125 0.000 0.000 
## 
## Node number 11799: 119 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3277311  P(node) =0.00595
##     class counts:    80    25    11     3     0
##    probabilities: 0.672 0.210 0.092 0.025 0.000 
##   left son=23598 (63 obs) right son=23599 (56 obs)
##   Primary splits:
##       reimbursement2008 < 1125   to the right, improve=0.8342670, (0 missing)
##       depression        < 0.5    to the right, improve=0.6215151, (0 missing)
##       age               < 91     to the right, improve=0.3560924, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.1876751, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1153637, (0 missing)
##   Surrogate splits:
##       age    < 75.5   to the right, agree=0.605, adj=0.161, (0 split)
##       cancer < 0.5    to the left,  agree=0.563, adj=0.071, (0 split)
## 
## Node number 12110: 36 observations,    complexity param=6.084576e-05
##   predicted class=B1  expected loss=0.3888889  P(node) =0.0018
##     class counts:    22    13     1     0     0
##    probabilities: 0.611 0.361 0.028 0.000 0.000 
##   left son=24220 (28 obs) right son=24221 (8 obs)
##   Primary splits:
##       reimbursement2008 < 1005   to the left,  improve=1.2976190, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.9564103, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6806240, (0 missing)
##       age               < 76.5   to the left,  improve=0.2583333, (0 missing)
## 
## Node number 12111: 79 observations,    complexity param=6.084576e-05
##   predicted class=B1  expected loss=0.3544304  P(node) =0.00395
##     class counts:    51    16    11     0     1
##    probabilities: 0.646 0.203 0.139 0.000 0.013 
##   left son=24222 (65 obs) right son=24223 (14 obs)
##   Primary splits:
##       age               < 71.5   to the left,  improve=1.1460840, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8533283, (0 missing)
##       kidney            < 0.5    to the right, improve=0.7541934, (0 missing)
##       depression        < 0.5    to the right, improve=0.7294694, (0 missing)
##       reimbursement2008 < 1075   to the right, improve=0.6940378, (0 missing)
## 
## Node number 12308: 15 observations
##   predicted class=B1  expected loss=0.1333333  P(node) =0.00075
##     class counts:    13     2     0     0     0
##    probabilities: 0.867 0.133 0.000 0.000 0.000 
## 
## Node number 12309: 44 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.4090909  P(node) =0.0022
##     class counts:    26    13     4     0     1
##    probabilities: 0.591 0.295 0.091 0.000 0.023 
##   left son=24618 (16 obs) right son=24619 (28 obs)
##   Primary splits:
##       diabetes          < 0.5    to the right, improve=1.4090910, (0 missing)
##       reimbursement2008 < 1940   to the left,  improve=1.2702020, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.8569674, (0 missing)
##       age               < 52.5   to the right, improve=0.4299242, (0 missing)
##   Surrogate splits:
##       alzheimers < 0.5    to the right, agree=0.75, adj=0.312, (0 split)
## 
## Node number 12336: 11 observations
##   predicted class=B1  expected loss=0.1818182  P(node) =0.00055
##     class counts:     9     2     0     0     0
##    probabilities: 0.818 0.182 0.000 0.000 0.000 
## 
## Node number 12337: 38 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.4473684  P(node) =0.0019
##     class counts:    21    13     4     0     0
##    probabilities: 0.553 0.342 0.105 0.000 0.000 
##   left son=24674 (29 obs) right son=24675 (9 obs)
##   Primary splits:
##       reimbursement2008 < 2020   to the left,  improve=0.85198630, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.59298250, (0 missing)
##       age               < 75.5   to the right, improve=0.46917290, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.21617090, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.04298246, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.789, adj=0.111, (0 split)
## 
## Node number 12724: 32 observations
##   predicted class=B1  expected loss=0.40625  P(node) =0.0016
##     class counts:    19     6     6     0     1
##    probabilities: 0.594 0.188 0.188 0.000 0.031 
## 
## Node number 12725: 13 observations
##   predicted class=B2  expected loss=0.4615385  P(node) =0.00065
##     class counts:     4     7     2     0     0
##    probabilities: 0.308 0.538 0.154 0.000 0.000 
## 
## Node number 12726: 36 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.5555556  P(node) =0.0018
##     class counts:    16    10     8     2     0
##    probabilities: 0.444 0.278 0.222 0.056 0.000 
##   left son=25452 (12 obs) right son=25453 (24 obs)
##   Primary splits:
##       reimbursement2008 < 2400   to the left,  improve=1.3055560, (0 missing)
##       age               < 67.5   to the left,  improve=1.1014790, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8040404, (0 missing)
##       depression        < 0.5    to the right, improve=0.5472222, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.4126984, (0 missing)
##   Surrogate splits:
##       osteoporosis < 0.5    to the right, agree=0.694, adj=0.083, (0 split)
## 
## Node number 12727: 24 observations
##   predicted class=B2  expected loss=0.4166667  P(node) =0.0012
##     class counts:     5    14     5     0     0
##    probabilities: 0.208 0.583 0.208 0.000 0.000 
## 
## Node number 13340: 34 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.4411765  P(node) =0.0017
##     class counts:    19    14     1     0     0
##    probabilities: 0.559 0.412 0.029 0.000 0.000 
##   left son=26680 (7 obs) right son=26681 (27 obs)
##   Primary splits:
##       reimbursement2008 < 2070   to the right, improve=0.96389670, (0 missing)
##       age               < 79.5   to the right, improve=0.48151590, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.41515840, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.41515840, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.06900452, (0 missing)
## 
## Node number 13341: 8 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0004
##     class counts:     2     4     1     1     0
##    probabilities: 0.250 0.500 0.125 0.125 0.000 
## 
## Node number 13378: 20 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.001
##     class counts:    15     5     0     0     0
##    probabilities: 0.750 0.250 0.000 0.000 0.000 
## 
## Node number 13379: 95 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.4842105  P(node) =0.00475
##     class counts:    49    27    11     7     1
##    probabilities: 0.516 0.284 0.116 0.074 0.011 
##   left son=26758 (27 obs) right son=26759 (68 obs)
##   Primary splits:
##       reimbursement2008 < 1735   to the left,  improve=2.2624360, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6768740, (0 missing)
##       age               < 67.5   to the left,  improve=0.6566828, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5342853, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.1812826, (0 missing)
## 
## Node number 13408: 55 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.5272727  P(node) =0.00275
##     class counts:    26    24     2     3     0
##    probabilities: 0.473 0.436 0.036 0.055 0.000 
##   left son=26816 (45 obs) right son=26817 (10 obs)
##   Primary splits:
##       reimbursement2008 < 1865   to the left,  improve=1.1555560, (0 missing)
##       age               < 66.5   to the right, improve=1.0879120, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4500000, (0 missing)
##       kidney            < 0.5    to the right, improve=0.3837209, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.3285714, (0 missing)
## 
## Node number 13409: 33 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5151515  P(node) =0.00165
##     class counts:    10    16     4     2     1
##    probabilities: 0.303 0.485 0.121 0.061 0.030 
##   left son=26818 (7 obs) right son=26819 (26 obs)
##   Primary splits:
##       age               < 72.5   to the right, improve=1.6307030, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.0479800, (0 missing)
##       reimbursement2008 < 1980   to the right, improve=0.9393939, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.8163591, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.5449883, (0 missing)
## 
## Node number 13702: 14 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.0007
##     class counts:    10     4     0     0     0
##    probabilities: 0.714 0.286 0.000 0.000 0.000 
## 
## Node number 13703: 10 observations
##   predicted class=B2  expected loss=0.4  P(node) =0.0005
##     class counts:     2     6     1     1     0
##    probabilities: 0.200 0.600 0.100 0.100 0.000 
## 
## Node number 13740: 7 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.00035
##     class counts:     5     0     2     0     0
##    probabilities: 0.714 0.000 0.286 0.000 0.000 
## 
## Node number 13741: 39 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.5128205  P(node) =0.00195
##     class counts:    14    19     6     0     0
##    probabilities: 0.359 0.487 0.154 0.000 0.000 
##   left son=27482 (15 obs) right son=27483 (24 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the right, improve=2.1782050, (0 missing)
##       reimbursement2008 < 2225   to the left,  improve=0.9035674, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.5156510, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.4871795, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4102564, (0 missing)
##   Surrogate splits:
##       age    < 81.5   to the right, agree=0.692, adj=0.200, (0 split)
##       stroke < 0.5    to the right, agree=0.641, adj=0.067, (0 split)
## 
## Node number 13742: 13 observations
##   predicted class=B1  expected loss=0.4615385  P(node) =0.00065
##     class counts:     7     6     0     0     0
##    probabilities: 0.538 0.462 0.000 0.000 0.000 
## 
## Node number 13743: 40 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.375  P(node) =0.002
##     class counts:     6    25     8     1     0
##    probabilities: 0.150 0.625 0.200 0.025 0.000 
##   left son=27486 (33 obs) right son=27487 (7 obs)
##   Primary splits:
##       age               < 78.5   to the left,  improve=1.5816020, (0 missing)
##       reimbursement2008 < 1955   to the left,  improve=1.1595240, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.1595240, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5166667, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.4983516, (0 missing)
## 
## Node number 13868: 30 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4666667  P(node) =0.0015
##     class counts:    16    11     3     0     0
##    probabilities: 0.533 0.367 0.100 0.000 0.000 
##   left son=27736 (22 obs) right son=27737 (8 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=1.3151520, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7696970, (0 missing)
##       reimbursement2008 < 2845   to the left,  improve=0.6333333, (0 missing)
##       age               < 73.5   to the left,  improve=0.2464555, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.2126984, (0 missing)
##   Surrogate splits:
##       copd              < 0.5    to the left,  agree=0.867, adj=0.500, (0 split)
##       reimbursement2008 < 3015   to the left,  agree=0.867, adj=0.500, (0 split)
##       bucket2008        < 1.5    to the left,  agree=0.833, adj=0.375, (0 split)
## 
## Node number 13869: 11 observations
##   predicted class=B2  expected loss=0.4545455  P(node) =0.00055
##     class counts:     2     6     3     0     0
##    probabilities: 0.182 0.545 0.273 0.000 0.000 
## 
## Node number 13874: 24 observations
##   predicted class=B1  expected loss=0.375  P(node) =0.0012
##     class counts:    15     3     5     0     1
##    probabilities: 0.625 0.125 0.208 0.000 0.042 
## 
## Node number 13875: 27 observations,    complexity param=0.0001014096
##   predicted class=B1  expected loss=0.5925926  P(node) =0.00135
##     class counts:    11     8     5     2     1
##    probabilities: 0.407 0.296 0.185 0.074 0.037 
##   left son=27750 (20 obs) right son=27751 (7 obs)
##   Primary splits:
##       reimbursement2008 < 3040   to the right, improve=1.3798940, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.1664490, (0 missing)
##       age               < 75.5   to the right, improve=0.8791423, (0 missing)
##       depression        < 0.5    to the right, improve=0.1656085, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1481481, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the right, agree=0.926, adj=0.714, (0 split)
## 
## Node number 13876: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     2     5     0     0     0
##    probabilities: 0.286 0.714 0.000 0.000 0.000 
## 
## Node number 13877: 26 observations,    complexity param=0.0002662002
##   predicted class=B1  expected loss=0.5769231  P(node) =0.0013
##     class counts:    11    10     4     1     0
##    probabilities: 0.423 0.385 0.154 0.038 0.000 
##   left son=27754 (12 obs) right son=27755 (14 obs)
##   Primary splits:
##       reimbursement2008 < 2785   to the left,  improve=1.203297, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.040598, (0 missing)
##       age               < 82.5   to the left,  improve=0.707265, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.769, adj=0.500, (0 split)
##       depression < 0.5    to the right, agree=0.615, adj=0.167, (0 split)
##       age        < 81     to the left,  agree=0.577, adj=0.083, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.577, adj=0.083, (0 split)
## 
## Node number 13962: 23 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.5217391  P(node) =0.00115
##     class counts:    10    11     1     1     0
##    probabilities: 0.435 0.478 0.043 0.043 0.000 
##   left son=27924 (9 obs) right son=27925 (14 obs)
##   Primary splits:
##       reimbursement2008 < 2630   to the left,  improve=1.8599030, (0 missing)
##       age               < 71.5   to the right, improve=1.5186340, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7505017, (0 missing)
##   Surrogate splits:
##       age < 71.5   to the left,  agree=0.652, adj=0.111, (0 split)
## 
## Node number 13963: 21 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4761905  P(node) =0.00105
##     class counts:    11     5     2     3     0
##    probabilities: 0.524 0.238 0.095 0.143 0.000 
##   left son=27926 (12 obs) right son=27927 (9 obs)
##   Primary splits:
##       age               < 71.5   to the right, improve=1.2619050, (0 missing)
##       depression        < 0.5    to the right, improve=0.5714286, (0 missing)
##       reimbursement2008 < 2850   to the right, improve=0.1428571, (0 missing)
##   Surrogate splits:
##       copd              < 0.5    to the left,  agree=0.619, adj=0.111, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.619, adj=0.111, (0 split)
##       reimbursement2008 < 2830   to the left,  agree=0.619, adj=0.111, (0 split)
## 
## Node number 13966: 10 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0005
##     class counts:     5     3     1     1     0
##    probabilities: 0.500 0.300 0.100 0.100 0.000 
## 
## Node number 13967: 35 observations
##   predicted class=B2  expected loss=0.3714286  P(node) =0.00175
##     class counts:     7    22     3     3     0
##    probabilities: 0.200 0.629 0.086 0.086 0.000 
## 
## Node number 14010: 8 observations
##   predicted class=B1  expected loss=0.375  P(node) =0.0004
##     class counts:     5     2     1     0     0
##    probabilities: 0.625 0.250 0.125 0.000 0.000 
## 
## Node number 14011: 12 observations
##   predicted class=B3  expected loss=0.6666667  P(node) =0.0006
##     class counts:     3     1     4     4     0
##    probabilities: 0.250 0.083 0.333 0.333 0.000 
## 
## Node number 14080: 18 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0009
##     class counts:    12     4     2     0     0
##    probabilities: 0.667 0.222 0.111 0.000 0.000 
## 
## Node number 14081: 14 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0007
##     class counts:     5     7     2     0     0
##    probabilities: 0.357 0.500 0.143 0.000 0.000 
## 
## Node number 14388: 32 observations
##   predicted class=B1  expected loss=0.4375  P(node) =0.0016
##     class counts:    18    11     2     1     0
##    probabilities: 0.562 0.344 0.062 0.031 0.000 
## 
## Node number 14389: 47 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4042553  P(node) =0.00235
##     class counts:    28     6    13     0     0
##    probabilities: 0.596 0.128 0.277 0.000 0.000 
##   left son=28778 (22 obs) right son=28779 (25 obs)
##   Primary splits:
##       age               < 70.5   to the right, improve=1.1429010, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9358252, (0 missing)
##       reimbursement2008 < 4425   to the right, improve=0.5714819, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.4947017, (0 missing)
##       kidney            < 0.5    to the right, improve=0.3933442, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 5070   to the left,  agree=0.596, adj=0.136, (0 split)
##       alzheimers        < 0.5    to the right, agree=0.574, adj=0.091, (0 split)
##       kidney            < 0.5    to the left,  agree=0.553, adj=0.045, (0 split)
## 
## Node number 15372: 20 observations
##   predicted class=B1  expected loss=0.3  P(node) =0.001
##     class counts:    14     3     2     1     0
##    probabilities: 0.700 0.150 0.100 0.050 0.000 
## 
## Node number 15373: 56 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5535714  P(node) =0.0028
##     class counts:    25    14    16     1     0
##    probabilities: 0.446 0.250 0.286 0.018 0.000 
##   left son=30746 (17 obs) right son=30747 (39 obs)
##   Primary splits:
##       reimbursement2008 < 3745   to the left,  improve=1.6851430, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.1778070, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5569382, (0 missing)
##       age               < 53.5   to the right, improve=0.4621212, (0 missing)
##       depression        < 0.5    to the left,  improve=0.1055556, (0 missing)
##   Surrogate splits:
##       age < 69.5   to the right, agree=0.714, adj=0.059, (0 split)
## 
## Node number 15426: 85 observations,    complexity param=0.0003295812
##   predicted class=B1  expected loss=0.4588235  P(node) =0.00425
##     class counts:    46    28    10     1     0
##    probabilities: 0.541 0.329 0.118 0.012 0.000 
##   left son=30852 (76 obs) right son=30853 (9 obs)
##   Primary splits:
##       reimbursement2008 < 29020  to the left,  improve=1.3666320, (0 missing)
##       age               < 82.5   to the left,  improve=0.8676149, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4882353, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.3426025, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.3141176, (0 missing)
##   Surrogate splits:
##       bucket2008 < 4.5    to the left,  agree=0.918, adj=0.222, (0 split)
## 
## Node number 15427: 21 observations,    complexity param=0.0003295812
##   predicted class=B1  expected loss=0.6666667  P(node) =0.00105
##     class counts:     7     7     1     6     0
##    probabilities: 0.333 0.333 0.048 0.286 0.000 
##   left son=30854 (13 obs) right son=30855 (8 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=1.2060440, (0 missing)
##       reimbursement2008 < 5580   to the left,  improve=0.7637363, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4285714, (0 missing)
##       age               < 79.5   to the right, improve=0.2936508, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1428571, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 5580   to the left,  agree=0.810, adj=0.500, (0 split)
##       stroke            < 0.5    to the left,  agree=0.714, adj=0.250, (0 split)
##       age               < 83.5   to the left,  agree=0.667, adj=0.125, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.667, adj=0.125, (0 split)
## 
## Node number 15450: 26 observations
##   predicted class=B2  expected loss=0.1923077  P(node) =0.0013
##     class counts:     3    21     2     0     0
##    probabilities: 0.115 0.808 0.077 0.000 0.000 
## 
## Node number 15451: 21 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5238095  P(node) =0.00105
##     class counts:     4    10     5     2     0
##    probabilities: 0.190 0.476 0.238 0.095 0.000 
##   left son=30902 (10 obs) right son=30903 (11 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.0406930, (0 missing)
##       reimbursement2008 < 10445  to the right, improve=0.2380952, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.1861472, (0 missing)
##       age               < 86.5   to the right, improve=0.1721612, (0 missing)
##   Surrogate splits:
##       age               < 86.5   to the right, agree=0.714, adj=0.4, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.619, adj=0.2, (0 split)
##       reimbursement2008 < 5600   to the left,  agree=0.619, adj=0.2, (0 split)
## 
## Node number 15452: 38 observations,    complexity param=0.0004056384
##   predicted class=B1  expected loss=0.6052632  P(node) =0.0019
##     class counts:    15    13     5     5     0
##    probabilities: 0.395 0.342 0.132 0.132 0.000 
##   left son=30904 (26 obs) right son=30905 (12 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the right, improve=1.3927130, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.2562660, (0 missing)
##       copd              < 0.5    to the left,  improve=1.1773280, (0 missing)
##       age               < 78.5   to the right, improve=0.7975822, (0 missing)
##       reimbursement2008 < 21895  to the left,  improve=0.5716817, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 7780   to the right, agree=0.763, adj=0.250, (0 split)
##       bucket2008        < 2.5    to the right, agree=0.737, adj=0.167, (0 split)
## 
## Node number 15453: 11 observations
##   predicted class=B2  expected loss=0.4545455  P(node) =0.00055
##     class counts:     0     6     2     2     1
##    probabilities: 0.000 0.545 0.182 0.182 0.091 
## 
## Node number 15482: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     2     2     3     0     0
##    probabilities: 0.286 0.286 0.429 0.000 0.000 
## 
## Node number 15483: 13 observations
##   predicted class=B2  expected loss=0.4615385  P(node) =0.00065
##     class counts:     3     7     1     2     0
##    probabilities: 0.231 0.538 0.077 0.154 0.000 
## 
## Node number 15574: 8 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0004
##     class counts:     1     4     2     1     0
##    probabilities: 0.125 0.500 0.250 0.125 0.000 
## 
## Node number 15575: 14 observations
##   predicted class=B3  expected loss=0.3571429  P(node) =0.0007
##     class counts:     1     3     9     1     0
##    probabilities: 0.071 0.214 0.643 0.071 0.000 
## 
## Node number 15576: 16 observations
##   predicted class=B3  expected loss=0.625  P(node) =0.0008
##     class counts:     5     5     6     0     0
##    probabilities: 0.312 0.312 0.375 0.000 0.000 
## 
## Node number 15577: 10 observations
##   predicted class=B2  expected loss=0.6  P(node) =0.0005
##     class counts:     1     4     3     2     0
##    probabilities: 0.100 0.400 0.300 0.200 0.000 
## 
## Node number 15762: 32 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5625  P(node) =0.0016
##     class counts:    12    14     3     2     1
##    probabilities: 0.375 0.438 0.094 0.062 0.031 
##   left son=31524 (8 obs) right son=31525 (24 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=2.0208330, (0 missing)
##       reimbursement2008 < 5625   to the left,  improve=1.1806370, (0 missing)
##       age               < 67     to the left,  improve=0.8541667, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6943627, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6344697, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 5120   to the left,  agree=0.781, adj=0.125, (0 split)
## 
## Node number 15763: 20 observations
##   predicted class=B2  expected loss=0.25  P(node) =0.001
##     class counts:     2    15     2     1     0
##    probabilities: 0.100 0.750 0.100 0.050 0.000 
## 
## Node number 15826: 12 observations
##   predicted class=B2  expected loss=0.4166667  P(node) =0.0006
##     class counts:     2     7     3     0     0
##    probabilities: 0.167 0.583 0.250 0.000 0.000 
## 
## Node number 15827: 10 observations
##   predicted class=B3  expected loss=0.5  P(node) =0.0005
##     class counts:     3     1     5     1     0
##    probabilities: 0.300 0.100 0.500 0.100 0.000 
## 
## Node number 15828: 53 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5283019  P(node) =0.00265
##     class counts:    14    25     7     6     1
##    probabilities: 0.264 0.472 0.132 0.113 0.019 
##   left son=31656 (10 obs) right son=31657 (43 obs)
##   Primary splits:
##       copd              < 0.5    to the right, improve=1.6914440, (0 missing)
##       age               < 84.5   to the right, improve=1.2423480, (0 missing)
##       reimbursement2008 < 4140   to the right, improve=1.2035630, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.4599632, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.4325067, (0 missing)
##   Surrogate splits:
##       age < 85.5   to the right, agree=0.83, adj=0.1, (0 split)
## 
## Node number 15829: 37 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5135135  P(node) =0.00185
##     class counts:     4    18    13     2     0
##    probabilities: 0.108 0.486 0.351 0.054 0.000 
##   left son=31658 (15 obs) right son=31659 (22 obs)
##   Primary splits:
##       age               < 74.5   to the right, improve=2.4139230, (0 missing)
##       reimbursement2008 < 9285   to the left,  improve=0.9525955, (0 missing)
##       copd              < 0.5    to the right, improve=0.9323379, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6526177, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.4084271, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 8600   to the right, agree=0.649, adj=0.133, (0 split)
##       cancer            < 0.5    to the right, agree=0.622, adj=0.067, (0 split)
## 
## Node number 15830: 46 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5869565  P(node) =0.0023
##     class counts:     7    19    18     2     0
##    probabilities: 0.152 0.413 0.391 0.043 0.000 
##   left son=31660 (10 obs) right son=31661 (36 obs)
##   Primary splits:
##       reimbursement2008 < 5620   to the left,  improve=1.5787440, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.4489460, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.2212840, (0 missing)
##       age               < 72.5   to the left,  improve=0.6469979, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5652174, (0 missing)
## 
## Node number 15831: 28 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.6785714  P(node) =0.0014
##     class counts:     9     6     8     4     1
##    probabilities: 0.321 0.214 0.286 0.143 0.036 
##   left son=31662 (9 obs) right son=31663 (19 obs)
##   Primary splits:
##       age               < 84.5   to the left,  improve=2.6829570, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.8841270, (0 missing)
##       reimbursement2008 < 9375   to the left,  improve=1.4047620, (0 missing)
##       copd              < 0.5    to the left,  improve=1.1730160, (0 missing)
##       ihd               < 0.5    to the right, improve=0.6785714, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 11245  to the right, agree=0.75, adj=0.222, (0 split)
## 
## Node number 15876: 13 observations
##   predicted class=B1  expected loss=0.5384615  P(node) =0.00065
##     class counts:     6     3     4     0     0
##    probabilities: 0.462 0.231 0.308 0.000 0.000 
## 
## Node number 15877: 11 observations
##   predicted class=B2  expected loss=0.5454545  P(node) =0.00055
##     class counts:     1     5     5     0     0
##    probabilities: 0.091 0.455 0.455 0.000 0.000 
## 
## Node number 15896: 24 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.5416667  P(node) =0.0012
##     class counts:    11     6     1     5     1
##    probabilities: 0.458 0.250 0.042 0.208 0.042 
##   left son=31792 (10 obs) right son=31793 (14 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.3904760, (0 missing)
##       reimbursement2008 < 8475   to the left,  improve=0.7083333, (0 missing)
##       age               < 76.5   to the left,  improve=0.7047619, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7047619, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.5291375, (0 missing)
##   Surrogate splits:
##       alzheimers        < 0.5    to the right, agree=0.708, adj=0.3, (0 split)
##       depression        < 0.5    to the right, agree=0.667, adj=0.2, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.667, adj=0.2, (0 split)
##       reimbursement2008 < 8545   to the left,  agree=0.625, adj=0.1, (0 split)
## 
## Node number 15897: 145 observations,    complexity param=0.0002738059
##   predicted class=B2  expected loss=0.5655172  P(node) =0.00725
##     class counts:    32    63    20    26     4
##    probabilities: 0.221 0.434 0.138 0.179 0.028 
##   left son=31794 (18 obs) right son=31795 (127 obs)
##   Primary splits:
##       stroke            < 0.5    to the right, improve=1.3643170, (0 missing)
##       age               < 69.5   to the right, improve=1.3391670, (0 missing)
##       reimbursement2008 < 12310  to the left,  improve=1.0866570, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7151354, (0 missing)
##       depression        < 0.5    to the right, improve=0.5171751, (0 missing)
## 
## Node number 15900: 10 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0005
##     class counts:     2     5     2     0     1
##    probabilities: 0.200 0.500 0.200 0.000 0.100 
## 
## Node number 15901: 24 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.625  P(node) =0.0012
##     class counts:     7     3     9     4     1
##    probabilities: 0.292 0.125 0.375 0.167 0.042 
##   left son=31802 (17 obs) right son=31803 (7 obs)
##   Primary splits:
##       cancer            < 0.5    to the left,  improve=1.3823530, (0 missing)
##       reimbursement2008 < 10140  to the left,  improve=1.3181820, (0 missing)
##       depression        < 0.5    to the left,  improve=0.3333333, (0 missing)
##       age               < 82.5   to the left,  improve=0.3000000, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1153846, (0 missing)
##   Surrogate splits:
##       age               < 78.5   to the right, agree=0.792, adj=0.286, (0 split)
##       reimbursement2008 < 12480  to the left,  agree=0.750, adj=0.143, (0 split)
## 
## Node number 15902: 38 observations,    complexity param=7.60572e-05
##   predicted class=B2  expected loss=0.4736842  P(node) =0.0019
##     class counts:     3    20    10     5     0
##    probabilities: 0.079 0.526 0.263 0.132 0.000 
##   left son=31804 (23 obs) right son=31805 (15 obs)
##   Primary splits:
##       reimbursement2008 < 13070  to the left,  improve=1.5183830, (0 missing)
##       depression        < 0.5    to the right, improve=0.6842105, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5789474, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.3616541, (0 missing)
##       age               < 81.5   to the left,  improve=0.3395253, (0 missing)
##   Surrogate splits:
##       depression < 0.5    to the right, agree=0.632, adj=0.067, (0 split)
## 
## Node number 15903: 19 observations
##   predicted class=B4  expected loss=0.5263158  P(node) =0.00095
##     class counts:     2     4     3     9     1
##    probabilities: 0.105 0.211 0.158 0.474 0.053 
## 
## Node number 15920: 25 observations,    complexity param=0.0003650745
##   predicted class=B2  expected loss=0.6  P(node) =0.00125
##     class counts:     8    10     3     3     1
##    probabilities: 0.320 0.400 0.120 0.120 0.040 
##   left son=31840 (12 obs) right son=31841 (13 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the right, improve=2.974872, (0 missing)
##       reimbursement2008 < 5050   to the right, improve=2.154359, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.596667, (0 missing)
##       copd              < 0.5    to the left,  improve=1.546667, (0 missing)
##       age               < 84.5   to the left,  improve=0.654359, (0 missing)
##   Surrogate splits:
##       age               < 83.5   to the left,  agree=0.64, adj=0.250, (0 split)
##       copd              < 0.5    to the left,  agree=0.64, adj=0.250, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.64, adj=0.250, (0 split)
##       reimbursement2008 < 5050   to the left,  agree=0.64, adj=0.250, (0 split)
##       cancer            < 0.5    to the right, agree=0.60, adj=0.167, (0 split)
## 
## Node number 15921: 23 observations
##   predicted class=B2  expected loss=0.3478261  P(node) =0.00115
##     class counts:     1    15     4     3     0
##    probabilities: 0.043 0.652 0.174 0.130 0.000 
## 
## Node number 15922: 94 observations,    complexity param=0.0003650745
##   predicted class=B2  expected loss=0.5744681  P(node) =0.0047
##     class counts:    22    40    17    13     2
##    probabilities: 0.234 0.426 0.181 0.138 0.021 
##   left son=31844 (47 obs) right son=31845 (47 obs)
##   Primary splits:
##       reimbursement2008 < 4080   to the left,  improve=2.3617020, (0 missing)
##       age               < 59.5   to the left,  improve=0.9410374, (0 missing)
##       copd              < 0.5    to the right, improve=0.7460624, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.7348936, (0 missing)
##       ihd               < 0.5    to the right, improve=0.5315420, (0 missing)
##   Surrogate splits:
##       depression    < 0.5    to the left,  agree=0.638, adj=0.277, (0 split)
##       copd          < 0.5    to the right, agree=0.628, adj=0.255, (0 split)
##       cancer        < 0.5    to the left,  agree=0.564, adj=0.128, (0 split)
##       age           < 59.5   to the left,  agree=0.553, adj=0.106, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.553, adj=0.106, (0 split)
## 
## Node number 15923: 68 observations,    complexity param=0.0003650745
##   predicted class=B3  expected loss=0.6617647  P(node) =0.0034
##     class counts:    13    18    23    12     2
##    probabilities: 0.191 0.265 0.338 0.176 0.029 
##   left son=31846 (39 obs) right son=31847 (29 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=2.0284240, (0 missing)
##       reimbursement2008 < 5310   to the left,  improve=1.4514850, (0 missing)
##       depression        < 0.5    to the right, improve=1.3449950, (0 missing)
##       age               < 76.5   to the right, improve=1.1528720, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.6729055, (0 missing)
##   Surrogate splits:
##       age               < 75.5   to the right, agree=0.632, adj=0.138, (0 split)
##       stroke            < 0.5    to the left,  agree=0.618, adj=0.103, (0 split)
##       reimbursement2008 < 5600   to the left,  agree=0.618, adj=0.103, (0 split)
##       ihd               < 0.5    to the right, agree=0.588, adj=0.034, (0 split)
## 
## Node number 16036: 22 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.4545455  P(node) =0.0011
##     class counts:     9    12     1     0     0
##    probabilities: 0.409 0.545 0.045 0.000 0.000 
##   left son=32072 (7 obs) right son=32073 (15 obs)
##   Primary splits:
##       reimbursement2008 < 3905   to the left,  improve=1.0606060, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9772727, (0 missing)
##       age               < 70     to the right, improve=0.4701299, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.1201299, (0 missing)
## 
## Node number 16037: 7 observations
##   predicted class=B2  expected loss=0.7142857  P(node) =0.00035
##     class counts:     1     2     2     2     0
##    probabilities: 0.143 0.286 0.286 0.286 0.000 
## 
## Node number 16038: 31 observations
##   predicted class=B2  expected loss=0.3548387  P(node) =0.00155
##     class counts:     3    20     5     2     1
##    probabilities: 0.097 0.645 0.161 0.065 0.032 
## 
## Node number 16039: 9 observations
##   predicted class=B3  expected loss=0.4444444  P(node) =0.00045
##     class counts:     1     2     5     1     0
##    probabilities: 0.111 0.222 0.556 0.111 0.000 
## 
## Node number 16106: 130 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5  P(node) =0.0065
##     class counts:    13    65    36    14     2
##    probabilities: 0.100 0.500 0.277 0.108 0.015 
##   left son=32212 (52 obs) right son=32213 (78 obs)
##   Primary splits:
##       reimbursement2008 < 10630  to the right, improve=1.0128210, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.7109522, (0 missing)
##       age               < 95.5   to the right, improve=0.6226356, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.4532726, (0 missing)
##       depression        < 0.5    to the left,  improve=0.3446886, (0 missing)
##   Surrogate splits:
##       age < 96.5   to the right, agree=0.608, adj=0.019, (0 split)
## 
## Node number 16107: 22 observations,    complexity param=0.0001521144
##   predicted class=B3  expected loss=0.5454545  P(node) =0.0011
##     class counts:     0     8    10     2     2
##    probabilities: 0.000 0.364 0.455 0.091 0.091 
##   left son=32214 (14 obs) right son=32215 (8 obs)
##   Primary splits:
##       reimbursement2008 < 14005  to the right, improve=1.5032470, (0 missing)
##       age               < 70     to the left,  improve=0.8142968, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.6151515, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5484848, (0 missing)
##       depression        < 0.5    to the right, improve=0.4318182, (0 missing)
##   Surrogate splits:
##       stroke < 0.5    to the left,  agree=0.682, adj=0.125, (0 split)
## 
## Node number 16258: 41 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.6341463  P(node) =0.00205
##     class counts:    15     7     9    10     0
##    probabilities: 0.366 0.171 0.220 0.244 0.000 
##   left son=32516 (23 obs) right son=32517 (18 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=2.0715210, (0 missing)
##       age               < 74.5   to the right, improve=1.6679890, (0 missing)
##       cancer            < 0.5    to the right, improve=1.0314710, (0 missing)
##       reimbursement2008 < 24805  to the right, improve=0.9024390, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4716698, (0 missing)
##   Surrogate splits:
##       age               < 78.5   to the left,  agree=0.610, adj=0.111, (0 split)
##       reimbursement2008 < 24395  to the left,  agree=0.610, adj=0.111, (0 split)
##       alzheimers        < 0.5    to the right, agree=0.585, adj=0.056, (0 split)
## 
## Node number 16259: 8 observations
##   predicted class=B4  expected loss=0.375  P(node) =0.0004
##     class counts:     1     0     2     5     0
##    probabilities: 0.125 0.000 0.250 0.625 0.000 
## 
## Node number 16280: 28 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.0014
##     class counts:     5    16     3     3     1
##    probabilities: 0.179 0.571 0.107 0.107 0.036 
## 
## Node number 16281: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     0     1     3     2     1
##    probabilities: 0.000 0.143 0.429 0.286 0.143 
## 
## Node number 16282: 39 observations,    complexity param=0.000380286
##   predicted class=B2  expected loss=0.7179487  P(node) =0.00195
##     class counts:     9    11     9     9     1
##    probabilities: 0.231 0.282 0.231 0.231 0.026 
##   left son=32564 (10 obs) right son=32565 (29 obs)
##   Primary splits:
##       age               < 80     to the left,  improve=1.7168880, (0 missing)
##       reimbursement2008 < 17795  to the right, improve=0.9267399, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.8587676, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4467399, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3426385, (0 missing)
##   Surrogate splits:
##       heart.failure < 0.5    to the left,  agree=0.769, adj=0.1, (0 split)
## 
## Node number 16283: 7 observations
##   predicted class=B4  expected loss=0.4285714  P(node) =0.00035
##     class counts:     0     0     3     4     0
##    probabilities: 0.000 0.000 0.429 0.571 0.000 
## 
## Node number 16288: 22 observations
##   predicted class=B2  expected loss=0.3636364  P(node) =0.0011
##     class counts:     2    14     6     0     0
##    probabilities: 0.091 0.636 0.273 0.000 0.000 
## 
## Node number 16289: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     1     2     3     0     1
##    probabilities: 0.143 0.286 0.429 0.000 0.143 
## 
## Node number 16292: 20 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.55  P(node) =0.001
##     class counts:     9     4     4     3     0
##    probabilities: 0.450 0.200 0.200 0.150 0.000 
##   left son=32584 (10 obs) right son=32585 (10 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=1.9000000, (0 missing)
##       copd              < 0.5    to the left,  improve=1.8166670, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.2186810, (0 missing)
##       reimbursement2008 < 18105  to the left,  improve=0.8166667, (0 missing)
##       age               < 79     to the left,  improve=0.5000000, (0 missing)
##   Surrogate splits:
##       alzheimers        < 0.5    to the right, agree=0.65, adj=0.3, (0 split)
##       reimbursement2008 < 18235  to the left,  agree=0.65, adj=0.3, (0 split)
##       age               < 93.5   to the right, agree=0.60, adj=0.2, (0 split)
##       copd              < 0.5    to the right, agree=0.60, adj=0.2, (0 split)
##       cancer            < 0.5    to the left,  agree=0.55, adj=0.1, (0 split)
## 
## Node number 16293: 35 observations
##   predicted class=B2  expected loss=0.4857143  P(node) =0.00175
##     class counts:     4    18     5     6     2
##    probabilities: 0.114 0.514 0.143 0.171 0.057 
## 
## Node number 16294: 9 observations
##   predicted class=B2  expected loss=0.2222222  P(node) =0.00045
##     class counts:     0     7     2     0     0
##    probabilities: 0.000 0.778 0.222 0.000 0.000 
## 
## Node number 16295: 25 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.68  P(node) =0.00125
##     class counts:     0     8     8     7     2
##    probabilities: 0.000 0.320 0.320 0.280 0.080 
##   left son=32590 (10 obs) right son=32591 (15 obs)
##   Primary splits:
##       age               < 82.5   to the left,  improve=1.0933330, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.8933333, (0 missing)
##       reimbursement2008 < 16595  to the right, improve=0.6171429, (0 missing)
##       depression        < 0.5    to the left,  improve=0.1885714, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.1276471, (0 missing)
##   Surrogate splits:
##       cancer            < 0.5    to the right, agree=0.68, adj=0.2, (0 split)
##       copd              < 0.5    to the right, agree=0.68, adj=0.2, (0 split)
##       reimbursement2008 < 17140  to the right, agree=0.68, adj=0.2, (0 split)
## 
## Node number 16374: 39 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5128205  P(node) =0.00195
##     class counts:     0    19     3    17     0
##    probabilities: 0.000 0.487 0.077 0.436 0.000 
##   left son=32748 (26 obs) right son=32749 (13 obs)
##   Primary splits:
##       age               < 63.5   to the right, improve=0.9487179, (0 missing)
##       reimbursement2008 < 43555  to the left,  improve=0.6509512, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5692308, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.3145206, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2601728, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 40920  to the right, agree=0.744, adj=0.231, (0 split)
## 
## Node number 16375: 19 observations
##   predicted class=B2  expected loss=0.7368421  P(node) =0.00095
##     class counts:     0     5     4     5     5
##    probabilities: 0.000 0.263 0.211 0.263 0.263 
## 
## Node number 16376: 139 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6546763  P(node) =0.00695
##     class counts:    14    48    36    36     5
##    probabilities: 0.101 0.345 0.259 0.259 0.036 
##   left son=32752 (7 obs) right son=32753 (132 obs)
##   Primary splits:
##       reimbursement2008 < 79435  to the right, improve=1.587483, (0 missing)
##       age               < 68.5   to the right, improve=1.331578, (0 missing)
##       bucket2008        < 4.5    to the right, improve=1.092884, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.060491, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.026367, (0 missing)
## 
## Node number 16377: 11 observations
##   predicted class=B3  expected loss=0.4545455  P(node) =0.00055
##     class counts:     0     1     6     2     2
##    probabilities: 0.000 0.091 0.545 0.182 0.182 
## 
## Node number 16378: 9 observations
##   predicted class=B3  expected loss=0.5555556  P(node) =0.00045
##     class counts:     0     2     4     2     1
##    probabilities: 0.000 0.222 0.444 0.222 0.111 
## 
## Node number 16379: 21 observations,    complexity param=0.0001521144
##   predicted class=B4  expected loss=0.4761905  P(node) =0.00105
##     class counts:     0     3     7    11     0
##    probabilities: 0.000 0.143 0.333 0.524 0.000 
##   left son=32758 (10 obs) right son=32759 (11 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=0.8580087, (0 missing)
##       age               < 85.5   to the left,  improve=0.5317460, (0 missing)
##       reimbursement2008 < 49045  to the left,  improve=0.4398268, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.2261905, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.1904762, (0 missing)
##   Surrogate splits:
##       cancer            < 0.5    to the right, agree=0.810, adj=0.6, (0 split)
##       arthritis         < 0.5    to the right, agree=0.667, adj=0.3, (0 split)
##       reimbursement2008 < 42665  to the left,  agree=0.619, adj=0.2, (0 split)
##       age               < 83.5   to the left,  agree=0.571, adj=0.1, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.571, adj=0.1, (0 split)
## 
## Node number 16380: 27 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.7037037  P(node) =0.00135
##     class counts:     2     8     8     8     1
##    probabilities: 0.074 0.296 0.296 0.296 0.037 
##   left son=32760 (19 obs) right son=32761 (8 obs)
##   Primary splits:
##       age               < 70     to the right, improve=0.9800195, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.9370370, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.8741582, (0 missing)
##       reimbursement2008 < 34375  to the left,  improve=0.5389978, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.3968855, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.741, adj=0.125, (0 split)
## 
## Node number 16381: 12 observations
##   predicted class=B4  expected loss=0.5  P(node) =0.0006
##     class counts:     2     2     0     6     2
##    probabilities: 0.167 0.167 0.000 0.500 0.167 
## 
## Node number 20570: 70 observations
##   predicted class=B1  expected loss=0.1714286  P(node) =0.0035
##     class counts:    58     7     5     0     0
##    probabilities: 0.829 0.100 0.071 0.000 0.000 
## 
## Node number 20571: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     1     4     2     0     0
##    probabilities: 0.143 0.571 0.286 0.000 0.000 
## 
## Node number 20574: 14 observations
##   predicted class=B1  expected loss=0.1428571  P(node) =0.0007
##     class counts:    12     2     0     0     0
##    probabilities: 0.857 0.143 0.000 0.000 0.000 
## 
## Node number 20575: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     2     5     0     1     0
##    probabilities: 0.250 0.625 0.000 0.125 0.000 
## 
## Node number 23598: 63 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.00315
##     class counts:    45    10     8     0     0
##    probabilities: 0.714 0.159 0.127 0.000 0.000 
## 
## Node number 23599: 56 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.375  P(node) =0.0028
##     class counts:    35    15     3     3     0
##    probabilities: 0.625 0.268 0.054 0.054 0.000 
##   left son=47198 (48 obs) right son=47199 (8 obs)
##   Primary splits:
##       age               < 80.5   to the left,  improve=1.1607140, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.7653061, (0 missing)
##       reimbursement2008 < 1095   to the left,  improve=0.6020408, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.4726553, (0 missing)
##       depression        < 0.5    to the right, improve=0.3311688, (0 missing)
## 
## Node number 24220: 28 observations
##   predicted class=B1  expected loss=0.3214286  P(node) =0.0014
##     class counts:    19     8     1     0     0
##    probabilities: 0.679 0.286 0.036 0.000 0.000 
## 
## Node number 24221: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     3     5     0     0     0
##    probabilities: 0.375 0.625 0.000 0.000 0.000 
## 
## Node number 24222: 65 observations,    complexity param=6.084576e-05
##   predicted class=B1  expected loss=0.3692308  P(node) =0.00325
##     class counts:    41    16     7     0     1
##    probabilities: 0.631 0.246 0.108 0.000 0.015 
##   left son=48444 (58 obs) right son=48445 (7 obs)
##   Primary splits:
##       reimbursement2008 < 1075   to the left,  improve=1.2435770, (0 missing)
##       copd              < 0.5    to the left,  improve=0.9029915, (0 missing)
##       depression        < 0.5    to the right, improve=0.8761474, (0 missing)
##       age               < 55.5   to the left,  improve=0.7910386, (0 missing)
##       kidney            < 0.5    to the right, improve=0.5612040, (0 missing)
## 
## Node number 24223: 14 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.0007
##     class counts:    10     0     4     0     0
##    probabilities: 0.714 0.000 0.286 0.000 0.000 
## 
## Node number 24618: 16 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.0008
##     class counts:    12     2     2     0     0
##    probabilities: 0.750 0.125 0.125 0.000 0.000 
## 
## Node number 24619: 28 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.5  P(node) =0.0014
##     class counts:    14    11     2     0     1
##    probabilities: 0.500 0.393 0.071 0.000 0.036 
##   left son=49238 (20 obs) right son=49239 (8 obs)
##   Primary splits:
##       reimbursement2008 < 1880   to the left,  improve=2.1500000, (0 missing)
##       age               < 50.5   to the right, improve=0.7857143, (0 missing)
## 
## Node number 24674: 29 observations
##   predicted class=B1  expected loss=0.3793103  P(node) =0.00145
##     class counts:    18     9     2     0     0
##    probabilities: 0.621 0.310 0.069 0.000 0.000 
## 
## Node number 24675: 9 observations
##   predicted class=B2  expected loss=0.5555556  P(node) =0.00045
##     class counts:     3     4     2     0     0
##    probabilities: 0.333 0.444 0.222 0.000 0.000 
## 
## Node number 25452: 12 observations
##   predicted class=B1  expected loss=0.4166667  P(node) =0.0006
##     class counts:     7     1     4     0     0
##    probabilities: 0.583 0.083 0.333 0.000 0.000 
## 
## Node number 25453: 24 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.625  P(node) =0.0012
##     class counts:     9     9     4     2     0
##    probabilities: 0.375 0.375 0.167 0.083 0.000 
##   left son=50906 (16 obs) right son=50907 (8 obs)
##   Primary splits:
##       age               < 70     to the left,  improve=0.5416667, (0 missing)
##       reimbursement2008 < 2545   to the right, improve=0.3326331, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.2916667, (0 missing)
##       depression        < 0.5    to the right, improve=0.1666667, (0 missing)
##   Surrogate splits:
##       stroke            < 0.5    to the left,  agree=0.75, adj=0.25, (0 split)
##       reimbursement2008 < 2525   to the right, agree=0.75, adj=0.25, (0 split)
## 
## Node number 26680: 7 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.00035
##     class counts:     5     1     1     0     0
##    probabilities: 0.714 0.143 0.143 0.000 0.000 
## 
## Node number 26681: 27 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.4814815  P(node) =0.00135
##     class counts:    14    13     0     0     0
##    probabilities: 0.519 0.481 0.000 0.000 0.000 
##   left son=53362 (20 obs) right son=53363 (7 obs)
##   Primary splits:
##       age               < 79.5   to the right, improve=1.02433900, (0 missing)
##       reimbursement2008 < 1950   to the left,  improve=1.02433900, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.05291005, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2040   to the left,  agree=0.815, adj=0.286, (0 split)
## 
## Node number 26758: 27 observations
##   predicted class=B1  expected loss=0.2962963  P(node) =0.00135
##     class counts:    19     4     3     0     1
##    probabilities: 0.704 0.148 0.111 0.000 0.037 
## 
## Node number 26759: 68 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5588235  P(node) =0.0034
##     class counts:    30    23     8     7     0
##    probabilities: 0.441 0.338 0.118 0.103 0.000 
##   left son=53518 (29 obs) right son=53519 (39 obs)
##   Primary splits:
##       reimbursement2008 < 2145   to the right, improve=1.4809120, (0 missing)
##       age               < 66.5   to the right, improve=1.4399320, (0 missing)
##       copd              < 0.5    to the left,  improve=0.7962224, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.4079739, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.2968627, (0 missing)
##   Surrogate splits:
##       age    < 72.5   to the right, agree=0.603, adj=0.069, (0 split)
##       cancer < 0.5    to the right, agree=0.588, adj=0.034, (0 split)
## 
## Node number 26816: 45 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5111111  P(node) =0.00225
##     class counts:    20    22     2     1     0
##    probabilities: 0.444 0.489 0.044 0.022 0.000 
##   left son=53632 (33 obs) right son=53633 (12 obs)
##   Primary splits:
##       age               < 66.5   to the right, improve=1.1686870, (0 missing)
##       reimbursement2008 < 1605   to the right, improve=0.5349850, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.2204060, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2016637, (0 missing)
##       kidney            < 0.5    to the right, improve=0.1888889, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1595   to the right, agree=0.778, adj=0.167, (0 split)
## 
## Node number 26817: 10 observations
##   predicted class=B1  expected loss=0.4  P(node) =0.0005
##     class counts:     6     2     0     2     0
##    probabilities: 0.600 0.200 0.000 0.200 0.000 
## 
## Node number 26818: 7 observations
##   predicted class=B2  expected loss=0.1428571  P(node) =0.00035
##     class counts:     1     6     0     0     0
##    probabilities: 0.143 0.857 0.000 0.000 0.000 
## 
## Node number 26819: 26 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.6153846  P(node) =0.0013
##     class counts:     9    10     4     2     1
##    probabilities: 0.346 0.385 0.154 0.077 0.038 
##   left son=53638 (14 obs) right son=53639 (12 obs)
##   Primary splits:
##       reimbursement2008 < 2005   to the right, improve=0.9926740, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.8057692, (0 missing)
##       age               < 67.5   to the right, improve=0.5337995, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.5095571, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3961828, (0 missing)
##   Surrogate splits:
##       diabetes   < 0.5    to the left,  agree=0.692, adj=0.333, (0 split)
##       age        < 66.5   to the right, agree=0.654, adj=0.250, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.577, adj=0.083, (0 split)
##       arthritis  < 0.5    to the left,  agree=0.577, adj=0.083, (0 split)
## 
## Node number 27482: 15 observations
##   predicted class=B1  expected loss=0.4  P(node) =0.00075
##     class counts:     9     5     1     0     0
##    probabilities: 0.600 0.333 0.067 0.000 0.000 
## 
## Node number 27483: 24 observations
##   predicted class=B2  expected loss=0.4166667  P(node) =0.0012
##     class counts:     5    14     5     0     0
##    probabilities: 0.208 0.583 0.208 0.000 0.000 
## 
## Node number 27486: 33 observations
##   predicted class=B2  expected loss=0.3030303  P(node) =0.00165
##     class counts:     4    23     5     1     0
##    probabilities: 0.121 0.697 0.152 0.030 0.000 
## 
## Node number 27487: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     2     2     3     0     0
##    probabilities: 0.286 0.286 0.429 0.000 0.000 
## 
## Node number 27736: 22 observations
##   predicted class=B1  expected loss=0.3636364  P(node) =0.0011
##     class counts:    14     7     1     0     0
##    probabilities: 0.636 0.318 0.045 0.000 0.000 
## 
## Node number 27737: 8 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0004
##     class counts:     2     4     2     0     0
##    probabilities: 0.250 0.500 0.250 0.000 0.000 
## 
## Node number 27750: 20 observations,    complexity param=0.0001014096
##   predicted class=B1  expected loss=0.5  P(node) =0.001
##     class counts:    10     6     2     2     0
##    probabilities: 0.500 0.300 0.100 0.100 0.000 
##   left son=55500 (8 obs) right son=55501 (12 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the right, improve=1.3833330, (0 missing)
##       reimbursement2008 < 3170   to the left,  improve=1.2166670, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5362637, (0 missing)
##       age               < 74.5   to the left,  improve=0.2343434, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1846154, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 3135   to the left,  agree=0.65, adj=0.125, (0 split)
## 
## Node number 27751: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     1     2     3     0     1
##    probabilities: 0.143 0.286 0.429 0.000 0.143 
## 
## Node number 27754: 12 observations
##   predicted class=B2  expected loss=0.4166667  P(node) =0.0006
##     class counts:     4     7     1     0     0
##    probabilities: 0.333 0.583 0.083 0.000 0.000 
## 
## Node number 27755: 14 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0007
##     class counts:     7     3     3     1     0
##    probabilities: 0.500 0.214 0.214 0.071 0.000 
## 
## Node number 27924: 9 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.00045
##     class counts:     6     2     0     1     0
##    probabilities: 0.667 0.222 0.000 0.111 0.000 
## 
## Node number 27925: 14 observations
##   predicted class=B2  expected loss=0.3571429  P(node) =0.0007
##     class counts:     4     9     1     0     0
##    probabilities: 0.286 0.643 0.071 0.000 0.000 
## 
## Node number 27926: 12 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0006
##     class counts:     8     1     1     2     0
##    probabilities: 0.667 0.083 0.083 0.167 0.000 
## 
## Node number 27927: 9 observations
##   predicted class=B2  expected loss=0.5555556  P(node) =0.00045
##     class counts:     3     4     1     1     0
##    probabilities: 0.333 0.444 0.111 0.111 0.000 
## 
## Node number 28778: 22 observations
##   predicted class=B1  expected loss=0.2727273  P(node) =0.0011
##     class counts:    16     2     4     0     0
##    probabilities: 0.727 0.091 0.182 0.000 0.000 
## 
## Node number 28779: 25 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.52  P(node) =0.00125
##     class counts:    12     4     9     0     0
##    probabilities: 0.480 0.160 0.360 0.000 0.000 
##   left son=57558 (18 obs) right son=57559 (7 obs)
##   Primary splits:
##       reimbursement2008 < 5500   to the left,  improve=1.6933330, (0 missing)
##       age               < 66.5   to the left,  improve=0.3984615, (0 missing)
##       copd              < 0.5    to the left,  improve=0.1516667, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.1238889, (0 missing)
##   Surrogate splits:
##       age < 69.5   to the left,  agree=0.76, adj=0.143, (0 split)
## 
## Node number 30746: 17 observations
##   predicted class=B1  expected loss=0.3529412  P(node) =0.00085
##     class counts:    11     4     2     0     0
##    probabilities: 0.647 0.235 0.118 0.000 0.000 
## 
## Node number 30747: 39 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.6410256  P(node) =0.00195
##     class counts:    14    10    14     1     0
##    probabilities: 0.359 0.256 0.359 0.026 0.000 
##   left son=61494 (16 obs) right son=61495 (23 obs)
##   Primary splits:
##       reimbursement2008 < 4475   to the right, improve=1.2231050, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.7420912, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.5071225, (0 missing)
##       age               < 66.5   to the right, improve=0.4089744, (0 missing)
##       depression        < 0.5    to the left,  improve=0.1756410, (0 missing)
##   Surrogate splits:
##       age < 64     to the right, agree=0.718, adj=0.312, (0 split)
## 
## Node number 30852: 76 observations,    complexity param=0.0003295812
##   predicted class=B1  expected loss=0.4210526  P(node) =0.0038
##     class counts:    44    24     8     0     0
##    probabilities: 0.579 0.316 0.105 0.000 0.000 
##   left son=61704 (48 obs) right son=61705 (28 obs)
##   Primary splits:
##       reimbursement2008 < 8850   to the right, improve=1.9802630, (0 missing)
##       age               < 82.5   to the left,  improve=1.1771250, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.6370279, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3385965, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.2719298, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.961, adj=0.893, (0 split)
##       age        < 74.5   to the right, agree=0.645, adj=0.036, (0 split)
##       ihd        < 0.5    to the right, agree=0.645, adj=0.036, (0 split)
## 
## Node number 30853: 9 observations
##   predicted class=B2  expected loss=0.5555556  P(node) =0.00045
##     class counts:     2     4     2     1     0
##    probabilities: 0.222 0.444 0.222 0.111 0.000 
## 
## Node number 30854: 13 observations
##   predicted class=B1  expected loss=0.5384615  P(node) =0.00065
##     class counts:     6     4     1     2     0
##    probabilities: 0.462 0.308 0.077 0.154 0.000 
## 
## Node number 30855: 8 observations
##   predicted class=B4  expected loss=0.5  P(node) =0.0004
##     class counts:     1     3     0     4     0
##    probabilities: 0.125 0.375 0.000 0.500 0.000 
## 
## Node number 30902: 10 observations
##   predicted class=B2  expected loss=0.3  P(node) =0.0005
##     class counts:     2     7     0     1     0
##    probabilities: 0.200 0.700 0.000 0.100 0.000 
## 
## Node number 30903: 11 observations
##   predicted class=B3  expected loss=0.5454545  P(node) =0.00055
##     class counts:     2     3     5     1     0
##    probabilities: 0.182 0.273 0.455 0.091 0.000 
## 
## Node number 30904: 26 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5  P(node) =0.0013
##     class counts:    13     7     3     3     0
##    probabilities: 0.500 0.269 0.115 0.115 0.000 
##   left son=61808 (18 obs) right son=61809 (8 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=1.7841880, (0 missing)
##       copd              < 0.5    to the left,  improve=1.6382280, (0 missing)
##       reimbursement2008 < 11300  to the left,  improve=0.6975130, (0 missing)
##       age               < 77.5   to the right, improve=0.5230769, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=0.2302665, (0 missing)
##   Surrogate splits:
##       age < 74.5   to the right, agree=0.769, adj=0.25, (0 split)
## 
## Node number 30905: 12 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0006
##     class counts:     2     6     2     2     0
##    probabilities: 0.167 0.500 0.167 0.167 0.000 
## 
## Node number 31524: 8 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.0004
##     class counts:     6     2     0     0     0
##    probabilities: 0.750 0.250 0.000 0.000 0.000 
## 
## Node number 31525: 24 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0012
##     class counts:     6    12     3     2     1
##    probabilities: 0.250 0.500 0.125 0.083 0.042 
## 
## Node number 31656: 10 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0005
##     class counts:     5     2     1     1     1
##    probabilities: 0.500 0.200 0.100 0.100 0.100 
## 
## Node number 31657: 43 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4651163  P(node) =0.00215
##     class counts:     9    23     6     5     0
##    probabilities: 0.209 0.535 0.140 0.116 0.000 
##   left son=63314 (36 obs) right son=63315 (7 obs)
##   Primary splits:
##       reimbursement2008 < 4140   to the right, improve=1.3715390, (0 missing)
##       age               < 78.5   to the right, improve=0.7748360, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.3783034, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.0576865, (0 missing)
## 
## Node number 31658: 15 observations
##   predicted class=B2  expected loss=0.2666667  P(node) =0.00075
##     class counts:     0    11     3     1     0
##    probabilities: 0.000 0.733 0.200 0.067 0.000 
## 
## Node number 31659: 22 observations
##   predicted class=B3  expected loss=0.5454545  P(node) =0.0011
##     class counts:     4     7    10     1     0
##    probabilities: 0.182 0.318 0.455 0.045 0.000 
## 
## Node number 31660: 10 observations
##   predicted class=B2  expected loss=0.3  P(node) =0.0005
##     class counts:     1     7     2     0     0
##    probabilities: 0.100 0.700 0.200 0.000 0.000 
## 
## Node number 31661: 36 observations,    complexity param=0.0002281716
##   predicted class=B3  expected loss=0.5555556  P(node) =0.0018
##     class counts:     6    12    16     2     0
##    probabilities: 0.167 0.333 0.444 0.056 0.000 
##   left son=63322 (21 obs) right son=63323 (15 obs)
##   Primary splits:
##       reimbursement2008 < 8035   to the right, improve=3.2825400, (0 missing)
##       bucket2008        < 2.5    to the right, improve=3.2825400, (0 missing)
##       cancer            < 0.5    to the right, improve=0.7777778, (0 missing)
##       age               < 68.5   to the left,  improve=0.5569986, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4777778, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=1.000, adj=1.000, (0 split)
##       age        < 69.5   to the left,  agree=0.611, adj=0.067, (0 split)
## 
## Node number 31662: 9 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.00045
##     class counts:     6     0     1     1     1
##    probabilities: 0.667 0.000 0.111 0.111 0.111 
## 
## Node number 31663: 19 observations
##   predicted class=B3  expected loss=0.6315789  P(node) =0.00095
##     class counts:     3     6     7     3     0
##    probabilities: 0.158 0.316 0.368 0.158 0.000 
## 
## Node number 31792: 10 observations
##   predicted class=B1  expected loss=0.3  P(node) =0.0005
##     class counts:     7     0     1     1     1
##    probabilities: 0.700 0.000 0.100 0.100 0.100 
## 
## Node number 31793: 14 observations
##   predicted class=B2  expected loss=0.5714286  P(node) =0.0007
##     class counts:     4     6     0     4     0
##    probabilities: 0.286 0.429 0.000 0.286 0.000 
## 
## Node number 31794: 18 observations
##   predicted class=B2  expected loss=0.3888889  P(node) =0.0009
##     class counts:     2    11     4     1     0
##    probabilities: 0.111 0.611 0.222 0.056 0.000 
## 
## Node number 31795: 127 observations,    complexity param=0.0002738059
##   predicted class=B2  expected loss=0.5905512  P(node) =0.00635
##     class counts:    30    52    16    25     4
##    probabilities: 0.236 0.409 0.126 0.197 0.031 
##   left son=63590 (65 obs) right son=63591 (62 obs)
##   Primary splits:
##       age               < 68.5   to the right, improve=1.8156310, (0 missing)
##       reimbursement2008 < 10940  to the left,  improve=1.2503720, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.8431131, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7185236, (0 missing)
##       depression        < 0.5    to the right, improve=0.7180088, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 9780   to the left,  agree=0.551, adj=0.081, (0 split)
##       depression        < 0.5    to the left,  agree=0.543, adj=0.065, (0 split)
##       cancer            < 0.5    to the left,  agree=0.535, adj=0.048, (0 split)
##       copd              < 0.5    to the left,  agree=0.528, adj=0.032, (0 split)
## 
## Node number 31802: 17 observations
##   predicted class=B1  expected loss=0.5882353  P(node) =0.00085
##     class counts:     7     2     5     2     1
##    probabilities: 0.412 0.118 0.294 0.118 0.059 
## 
## Node number 31803: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     0     1     4     2     0
##    probabilities: 0.000 0.143 0.571 0.286 0.000 
## 
## Node number 31804: 23 observations,    complexity param=7.60572e-05
##   predicted class=B2  expected loss=0.4347826  P(node) =0.00115
##     class counts:     2    13     8     0     0
##    probabilities: 0.087 0.565 0.348 0.000 0.000 
##   left son=63608 (13 obs) right son=63609 (10 obs)
##   Primary splits:
##       reimbursement2008 < 11420  to the left,  improve=0.8956522, (0 missing)
##       copd              < 0.5    to the right, improve=0.8320158, (0 missing)
##       age               < 81.5   to the left,  improve=0.7110368, (0 missing)
##       depression        < 0.5    to the left,  improve=0.3940649, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2033445, (0 missing)
##   Surrogate splits:
##       age    < 80.5   to the left,  agree=0.783, adj=0.5, (0 split)
##       stroke < 0.5    to the left,  agree=0.609, adj=0.1, (0 split)
## 
## Node number 31805: 15 observations
##   predicted class=B2  expected loss=0.5333333  P(node) =0.00075
##     class counts:     1     7     2     5     0
##    probabilities: 0.067 0.467 0.133 0.333 0.000 
## 
## Node number 31840: 12 observations
##   predicted class=B1  expected loss=0.4166667  P(node) =0.0006
##     class counts:     7     2     1     2     0
##    probabilities: 0.583 0.167 0.083 0.167 0.000 
## 
## Node number 31841: 13 observations
##   predicted class=B2  expected loss=0.3846154  P(node) =0.00065
##     class counts:     1     8     2     1     1
##    probabilities: 0.077 0.615 0.154 0.077 0.077 
## 
## Node number 31844: 47 observations,    complexity param=0.0003650745
##   predicted class=B1  expected loss=0.6808511  P(node) =0.00235
##     class counts:    15    14    10     6     2
##    probabilities: 0.319 0.298 0.213 0.128 0.043 
##   left son=63688 (7 obs) right son=63689 (40 obs)
##   Primary splits:
##       age               < 60.5   to the left,  improve=1.8709730, (0 missing)
##       reimbursement2008 < 4015   to the right, improve=1.6709730, (0 missing)
##       depression        < 0.5    to the right, improve=0.9065717, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6749409, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.3897557, (0 missing)
## 
## Node number 31845: 47 observations
##   predicted class=B2  expected loss=0.4468085  P(node) =0.00235
##     class counts:     7    26     7     7     0
##    probabilities: 0.149 0.553 0.149 0.149 0.000 
## 
## Node number 31846: 39 observations,    complexity param=0.0003650745
##   predicted class=B2  expected loss=0.6923077  P(node) =0.00195
##     class counts:    11    12     9     6     1
##    probabilities: 0.282 0.308 0.231 0.154 0.026 
##   left son=63692 (15 obs) right son=63693 (24 obs)
##   Primary splits:
##       age               < 76.5   to the right, improve=1.3128210, (0 missing)
##       depression        < 0.5    to the right, improve=1.0842490, (0 missing)
##       reimbursement2008 < 5315   to the left,  improve=0.9900135, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5262614, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.1901824, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 5155   to the left,  agree=0.718, adj=0.267, (0 split)
##       stroke            < 0.5    to the right, agree=0.667, adj=0.133, (0 split)
##       ihd               < 0.5    to the left,  agree=0.641, adj=0.067, (0 split)
## 
## Node number 31847: 29 observations
##   predicted class=B3  expected loss=0.5172414  P(node) =0.00145
##     class counts:     2     6    14     6     1
##    probabilities: 0.069 0.207 0.483 0.207 0.034 
## 
## Node number 32072: 7 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.00035
##     class counts:     4     2     1     0     0
##    probabilities: 0.571 0.286 0.143 0.000 0.000 
## 
## Node number 32073: 15 observations
##   predicted class=B2  expected loss=0.3333333  P(node) =0.00075
##     class counts:     5    10     0     0     0
##    probabilities: 0.333 0.667 0.000 0.000 0.000 
## 
## Node number 32212: 52 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4615385  P(node) =0.0026
##     class counts:     8    28    10     5     1
##    probabilities: 0.154 0.538 0.192 0.096 0.019 
##   left son=64424 (14 obs) right son=64425 (38 obs)
##   Primary splits:
##       reimbursement2008 < 11260  to the left,  improve=2.5399070, (0 missing)
##       alzheimers        < 0.5    to the right, improve=2.0053420, (0 missing)
##       depression        < 0.5    to the right, improve=0.6965171, (0 missing)
##       age               < 75.5   to the left,  improve=0.5668498, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5579070, (0 missing)
##   Surrogate splits:
##       age < 57     to the left,  agree=0.75, adj=0.071, (0 split)
## 
## Node number 32213: 78 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.525641  P(node) =0.0039
##     class counts:     5    37    26     9     1
##    probabilities: 0.064 0.474 0.333 0.115 0.013 
##   left son=64426 (37 obs) right son=64427 (41 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=0.6238358, (0 missing)
##       age               < 79.5   to the left,  improve=0.6101157, (0 missing)
##       reimbursement2008 < 10045  to the right, improve=0.6069777, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3743760, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.3659016, (0 missing)
##   Surrogate splits:
##       age               < 76     to the left,  agree=0.628, adj=0.216, (0 split)
##       reimbursement2008 < 9585   to the right, agree=0.590, adj=0.135, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.564, adj=0.081, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.551, adj=0.054, (0 split)
##       copd              < 0.5    to the left,  agree=0.538, adj=0.027, (0 split)
## 
## Node number 32214: 14 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0007
##     class counts:     0     7     5     0     2
##    probabilities: 0.000 0.500 0.357 0.000 0.143 
## 
## Node number 32215: 8 observations
##   predicted class=B3  expected loss=0.375  P(node) =0.0004
##     class counts:     0     1     5     2     0
##    probabilities: 0.000 0.125 0.625 0.250 0.000 
## 
## Node number 32516: 23 observations
##   predicted class=B1  expected loss=0.4782609  P(node) =0.00115
##     class counts:    12     2     3     6     0
##    probabilities: 0.522 0.087 0.130 0.261 0.000 
## 
## Node number 32517: 18 observations
##   predicted class=B3  expected loss=0.6666667  P(node) =0.0009
##     class counts:     3     5     6     4     0
##    probabilities: 0.167 0.278 0.333 0.222 0.000 
## 
## Node number 32564: 10 observations
##   predicted class=B3  expected loss=0.5  P(node) =0.0005
##     class counts:     2     3     5     0     0
##    probabilities: 0.200 0.300 0.500 0.000 0.000 
## 
## Node number 32565: 29 observations,    complexity param=0.000380286
##   predicted class=B4  expected loss=0.6896552  P(node) =0.00145
##     class counts:     7     8     4     9     1
##    probabilities: 0.241 0.276 0.138 0.310 0.034 
##   left son=65130 (22 obs) right son=65131 (7 obs)
##   Primary splits:
##       age               < 83.5   to the right, improve=1.5293330, (0 missing)
##       reimbursement2008 < 17795  to the right, improve=1.3395230, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5796935, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5726228, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.4006085, (0 missing)
## 
## Node number 32584: 10 observations
##   predicted class=B2  expected loss=0.6  P(node) =0.0005
##     class counts:     3     4     3     0     0
##    probabilities: 0.300 0.400 0.300 0.000 0.000 
## 
## Node number 32585: 10 observations
##   predicted class=B1  expected loss=0.4  P(node) =0.0005
##     class counts:     6     0     1     3     0
##    probabilities: 0.600 0.000 0.100 0.300 0.000 
## 
## Node number 32590: 10 observations
##   predicted class=B3  expected loss=0.5  P(node) =0.0005
##     class counts:     0     3     5     1     1
##    probabilities: 0.000 0.300 0.500 0.100 0.100 
## 
## Node number 32591: 15 observations
##   predicted class=B4  expected loss=0.6  P(node) =0.00075
##     class counts:     0     5     3     6     1
##    probabilities: 0.000 0.333 0.200 0.400 0.067 
## 
## Node number 32748: 26 observations
##   predicted class=B2  expected loss=0.4615385  P(node) =0.0013
##     class counts:     0    14     3     9     0
##    probabilities: 0.000 0.538 0.115 0.346 0.000 
## 
## Node number 32749: 13 observations
##   predicted class=B4  expected loss=0.3846154  P(node) =0.00065
##     class counts:     0     5     0     8     0
##    probabilities: 0.000 0.385 0.000 0.615 0.000 
## 
## Node number 32752: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     0     5     0     2     0
##    probabilities: 0.000 0.714 0.000 0.286 0.000 
## 
## Node number 32753: 132 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6742424  P(node) =0.0066
##     class counts:    14    43    36    34     5
##    probabilities: 0.106 0.326 0.273 0.258 0.038 
##   left son=65506 (72 obs) right son=65507 (60 obs)
##   Primary splits:
##       age               < 68.5   to the right, improve=1.3924240, (0 missing)
##       reimbursement2008 < 55300  to the right, improve=1.1164590, (0 missing)
##       bucket2008        < 4.5    to the right, improve=1.1164590, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9824242, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.9510963, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 65275  to the left,  agree=0.621, adj=0.167, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.561, adj=0.033, (0 split)
## 
## Node number 32758: 10 observations
##   predicted class=B3  expected loss=0.5  P(node) =0.0005
##     class counts:     0     1     5     4     0
##    probabilities: 0.000 0.100 0.500 0.400 0.000 
## 
## Node number 32759: 11 observations
##   predicted class=B4  expected loss=0.3636364  P(node) =0.00055
##     class counts:     0     2     2     7     0
##    probabilities: 0.000 0.182 0.182 0.636 0.000 
## 
## Node number 32760: 19 observations
##   predicted class=B3  expected loss=0.6315789  P(node) =0.00095
##     class counts:     2     6     7     4     0
##    probabilities: 0.105 0.316 0.368 0.211 0.000 
## 
## Node number 32761: 8 observations
##   predicted class=B4  expected loss=0.5  P(node) =0.0004
##     class counts:     0     2     1     4     1
##    probabilities: 0.000 0.250 0.125 0.500 0.125 
## 
## Node number 47198: 48 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0024
##     class counts:    32    11     3     2     0
##    probabilities: 0.667 0.229 0.062 0.042 0.000 
##   left son=94396 (38 obs) right son=94397 (10 obs)
##   Primary splits:
##       age               < 74.5   to the left,  improve=0.9486842, (0 missing)
##       reimbursement2008 < 975    to the right, improve=0.4675926, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2881868, (0 missing)
##       depression        < 0.5    to the right, improve=0.1600123, (0 missing)
## 
## Node number 47199: 8 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0004
##     class counts:     3     4     0     1     0
##    probabilities: 0.375 0.500 0.000 0.125 0.000 
## 
## Node number 48444: 58 observations
##   predicted class=B1  expected loss=0.3448276  P(node) =0.0029
##     class counts:    38    12     7     0     1
##    probabilities: 0.655 0.207 0.121 0.000 0.017 
## 
## Node number 48445: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     3     4     0     0     0
##    probabilities: 0.429 0.571 0.000 0.000 0.000 
## 
## Node number 49238: 20 observations
##   predicted class=B1  expected loss=0.35  P(node) =0.001
##     class counts:    13     7     0     0     0
##    probabilities: 0.650 0.350 0.000 0.000 0.000 
## 
## Node number 49239: 8 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0004
##     class counts:     1     4     2     0     1
##    probabilities: 0.125 0.500 0.250 0.000 0.125 
## 
## Node number 50906: 16 observations
##   predicted class=B2  expected loss=0.5625  P(node) =0.0008
##     class counts:     6     7     3     0     0
##    probabilities: 0.375 0.438 0.188 0.000 0.000 
## 
## Node number 50907: 8 observations
##   predicted class=B1  expected loss=0.625  P(node) =0.0004
##     class counts:     3     2     1     2     0
##    probabilities: 0.375 0.250 0.125 0.250 0.000 
## 
## Node number 53362: 20 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.4  P(node) =0.001
##     class counts:    12     8     0     0     0
##    probabilities: 0.600 0.400 0.000 0.000 0.000 
##   left son=106724 (9 obs) right son=106725 (11 obs)
##   Primary splits:
##       reimbursement2008 < 1790   to the left,  improve=1.0343430, (0 missing)
##       age               < 83.5   to the left,  improve=0.2813187, (0 missing)
##   Surrogate splits:
##       alzheimers < 0.5    to the right, agree=0.65, adj=0.222, (0 split)
##       age        < 81.5   to the right, agree=0.60, adj=0.111, (0 split)
## 
## Node number 53363: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     2     5     0     0     0
##    probabilities: 0.286 0.714 0.000 0.000 0.000 
## 
## Node number 53518: 29 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4482759  P(node) =0.00145
##     class counts:    16     7     5     1     0
##    probabilities: 0.552 0.241 0.172 0.034 0.000 
##   left son=107036 (17 obs) right son=107037 (12 obs)
##   Primary splits:
##       age               < 69.5   to the right, improve=1.65483400, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.09270000, (0 missing)
##       reimbursement2008 < 2385   to the left,  improve=0.89789520, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.59811170, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.04075235, (0 missing)
##   Surrogate splits:
##       arthritis         < 0.5    to the left,  agree=0.690, adj=0.250, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.655, adj=0.167, (0 split)
##       reimbursement2008 < 2405   to the left,  agree=0.655, adj=0.167, (0 split)
## 
## Node number 53519: 39 observations,    complexity param=0.0002028192
##   predicted class=B2  expected loss=0.5897436  P(node) =0.00195
##     class counts:    14    16     3     6     0
##    probabilities: 0.359 0.410 0.077 0.154 0.000 
##   left son=107038 (30 obs) right son=107039 (9 obs)
##   Primary splits:
##       reimbursement2008 < 2065   to the left,  improve=1.03418800, (0 missing)
##       age               < 67.5   to the right, improve=0.29641030, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.26290380, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.14529910, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.07020336, (0 missing)
##   Surrogate splits:
##       age < 64.5   to the right, agree=0.795, adj=0.111, (0 split)
## 
## Node number 53632: 33 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.4848485  P(node) =0.00165
##     class counts:    17    14     1     1     0
##    probabilities: 0.515 0.424 0.030 0.030 0.000 
##   left son=107264 (18 obs) right son=107265 (15 obs)
##   Primary splits:
##       reimbursement2008 < 1715   to the left,  improve=0.7535354, (0 missing)
##       age               < 70.5   to the left,  improve=0.5151515, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1724242, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.1471861, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.0479798, (0 missing)
##   Surrogate splits:
##       age      < 70.5   to the left,  agree=0.697, adj=0.333, (0 split)
##       diabetes < 0.5    to the left,  agree=0.636, adj=0.200, (0 split)
##       kidney   < 0.5    to the right, agree=0.576, adj=0.067, (0 split)
## 
## Node number 53633: 12 observations
##   predicted class=B2  expected loss=0.3333333  P(node) =0.0006
##     class counts:     3     8     1     0     0
##    probabilities: 0.250 0.667 0.083 0.000 0.000 
## 
## Node number 53638: 14 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0007
##     class counts:     7     5     1     1     0
##    probabilities: 0.500 0.357 0.071 0.071 0.000 
## 
## Node number 53639: 12 observations
##   predicted class=B2  expected loss=0.5833333  P(node) =0.0006
##     class counts:     2     5     3     1     1
##    probabilities: 0.167 0.417 0.250 0.083 0.083 
## 
## Node number 55500: 8 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.0004
##     class counts:     6     1     0     1     0
##    probabilities: 0.750 0.125 0.000 0.125 0.000 
## 
## Node number 55501: 12 observations
##   predicted class=B2  expected loss=0.5833333  P(node) =0.0006
##     class counts:     4     5     2     1     0
##    probabilities: 0.333 0.417 0.167 0.083 0.000 
## 
## Node number 57558: 18 observations
##   predicted class=B1  expected loss=0.3888889  P(node) =0.0009
##     class counts:    11     2     5     0     0
##    probabilities: 0.611 0.111 0.278 0.000 0.000 
## 
## Node number 57559: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     1     2     4     0     0
##    probabilities: 0.143 0.286 0.571 0.000 0.000 
## 
## Node number 61494: 16 observations
##   predicted class=B1  expected loss=0.625  P(node) =0.0008
##     class counts:     6     6     3     1     0
##    probabilities: 0.375 0.375 0.188 0.062 0.000 
## 
## Node number 61495: 23 observations,    complexity param=0.0001521144
##   predicted class=B3  expected loss=0.5217391  P(node) =0.00115
##     class counts:     8     4    11     0     0
##    probabilities: 0.348 0.174 0.478 0.000 0.000 
##   left son=122990 (10 obs) right son=122991 (13 obs)
##   Primary splits:
##       age               < 59     to the left,  improve=0.98394650, (0 missing)
##       reimbursement2008 < 4195   to the right, improve=0.83229810, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.64420290, (0 missing)
##       depression        < 0.5    to the right, improve=0.05452036, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.04420290, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4100   to the right, agree=0.652, adj=0.2, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.609, adj=0.1, (0 split)
## 
## Node number 61704: 48 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0024
##     class counts:    32    11     5     0     0
##    probabilities: 0.667 0.229 0.104 0.000 0.000 
## 
## Node number 61705: 28 observations,    complexity param=0.0003295812
##   predicted class=B2  expected loss=0.5357143  P(node) =0.0014
##     class counts:    12    13     3     0     0
##    probabilities: 0.429 0.464 0.107 0.000 0.000 
##   left son=123410 (13 obs) right son=123411 (15 obs)
##   Primary splits:
##       reimbursement2008 < 6985   to the left,  improve=4.0794870, (0 missing)
##       copd              < 0.5    to the left,  improve=0.9812834, (0 missing)
##       age               < 80.5   to the left,  improve=0.5000000, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4692308, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.3750000, (0 missing)
##   Surrogate splits:
##       heart.failure < 0.5    to the left,  agree=0.643, adj=0.231, (0 split)
##       age           < 83     to the right, agree=0.571, adj=0.077, (0 split)
##       bucket2008    < 2.5    to the left,  agree=0.571, adj=0.077, (0 split)
## 
## Node number 61808: 18 observations
##   predicted class=B1  expected loss=0.3888889  P(node) =0.0009
##     class counts:    11     4     0     3     0
##    probabilities: 0.611 0.222 0.000 0.167 0.000 
## 
## Node number 61809: 8 observations
##   predicted class=B2  expected loss=0.625  P(node) =0.0004
##     class counts:     2     3     3     0     0
##    probabilities: 0.250 0.375 0.375 0.000 0.000 
## 
## Node number 63314: 36 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4166667  P(node) =0.0018
##     class counts:     8    21     5     2     0
##    probabilities: 0.222 0.583 0.139 0.056 0.000 
##   left son=126628 (13 obs) right son=126629 (23 obs)
##   Primary splits:
##       reimbursement2008 < 5440   to the left,  improve=1.9760310, (0 missing)
##       age               < 74.5   to the left,  improve=0.7500000, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.5921212, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.1449948, (0 missing)
##   Surrogate splits:
##       age        < 81.5   to the right, agree=0.667, adj=0.077, (0 split)
##       cancer     < 0.5    to the right, agree=0.667, adj=0.077, (0 split)
##       stroke     < 0.5    to the right, agree=0.667, adj=0.077, (0 split)
##       bucket2008 < 2.5    to the left,  agree=0.667, adj=0.077, (0 split)
## 
## Node number 63315: 7 observations
##   predicted class=B4  expected loss=0.5714286  P(node) =0.00035
##     class counts:     1     2     1     3     0
##    probabilities: 0.143 0.286 0.143 0.429 0.000 
## 
## Node number 63322: 21 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5238095  P(node) =0.00105
##     class counts:     4    10     5     2     0
##    probabilities: 0.190 0.476 0.238 0.095 0.000 
##   left son=126644 (9 obs) right son=126645 (12 obs)
##   Primary splits:
##       age               < 67.5   to the left,  improve=1.4841270, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8174603, (0 missing)
##       reimbursement2008 < 11715  to the left,  improve=0.6529304, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4406926, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.2619048, (0 missing)
##   Surrogate splits:
##       cancer            < 0.5    to the right, agree=0.714, adj=0.333, (0 split)
##       reimbursement2008 < 10315  to the left,  agree=0.714, adj=0.333, (0 split)
##       osteoporosis      < 0.5    to the right, agree=0.619, adj=0.111, (0 split)
## 
## Node number 63323: 15 observations
##   predicted class=B3  expected loss=0.2666667  P(node) =0.00075
##     class counts:     2     2    11     0     0
##    probabilities: 0.133 0.133 0.733 0.000 0.000 
## 
## Node number 63590: 65 observations,    complexity param=0.0002738059
##   predicted class=B2  expected loss=0.5230769  P(node) =0.00325
##     class counts:    16    31    10     7     1
##    probabilities: 0.246 0.477 0.154 0.108 0.015 
##   left son=127180 (39 obs) right son=127181 (26 obs)
##   Primary splits:
##       reimbursement2008 < 10335  to the left,  improve=2.6871790, (0 missing)
##       age               < 71.5   to the left,  improve=1.7206540, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.6230770, (0 missing)
##       ihd               < 0.5    to the right, improve=1.3879500, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.8410256, (0 missing)
##   Surrogate splits:
##       alzheimers < 0.5    to the left,  agree=0.631, adj=0.077, (0 split)
##       copd       < 0.5    to the left,  agree=0.631, adj=0.077, (0 split)
##       bucket2008 < 2.5    to the left,  agree=0.631, adj=0.077, (0 split)
##       cancer     < 0.5    to the left,  agree=0.615, adj=0.038, (0 split)
## 
## Node number 63591: 62 observations,    complexity param=0.0002738059
##   predicted class=B2  expected loss=0.6612903  P(node) =0.0031
##     class counts:    14    21     6    18     3
##    probabilities: 0.226 0.339 0.097 0.290 0.048 
##   left son=127182 (28 obs) right son=127183 (34 obs)
##   Primary splits:
##       reimbursement2008 < 10290  to the right, improve=1.5262940, (0 missing)
##       age               < 52     to the left,  improve=1.5139440, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.4593000, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9970196, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5110357, (0 missing)
##   Surrogate splits:
##       bucket2008    < 2.5    to the right, agree=0.694, adj=0.321, (0 split)
##       cancer        < 0.5    to the right, agree=0.613, adj=0.143, (0 split)
##       heart.failure < 0.5    to the right, agree=0.597, adj=0.107, (0 split)
##       age           < 64.5   to the right, agree=0.581, adj=0.071, (0 split)
##       copd          < 0.5    to the right, agree=0.581, adj=0.071, (0 split)
## 
## Node number 63608: 13 observations
##   predicted class=B2  expected loss=0.3076923  P(node) =0.00065
##     class counts:     1     9     3     0     0
##    probabilities: 0.077 0.692 0.231 0.000 0.000 
## 
## Node number 63609: 10 observations
##   predicted class=B3  expected loss=0.5  P(node) =0.0005
##     class counts:     1     4     5     0     0
##    probabilities: 0.100 0.400 0.500 0.000 0.000 
## 
## Node number 63688: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     1     5     1     0     0
##    probabilities: 0.143 0.714 0.143 0.000 0.000 
## 
## Node number 63689: 40 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.65  P(node) =0.002
##     class counts:    14     9     9     6     2
##    probabilities: 0.350 0.225 0.225 0.150 0.050 
##   left son=127378 (14 obs) right son=127379 (26 obs)
##   Primary splits:
##       age               < 71.5   to the left,  improve=1.6214290, (0 missing)
##       reimbursement2008 < 3615   to the right, improve=1.0129630, (0 missing)
##       depression        < 0.5    to the right, improve=0.7313187, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5512788, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.3700000, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4015   to the right, agree=0.700, adj=0.143, (0 split)
##       osteoporosis      < 0.5    to the right, agree=0.675, adj=0.071, (0 split)
## 
## Node number 63692: 15 observations
##   predicted class=B3  expected loss=0.6  P(node) =0.00075
##     class counts:     4     5     6     0     0
##    probabilities: 0.267 0.333 0.400 0.000 0.000 
## 
## Node number 63693: 24 observations,    complexity param=0.0003650745
##   predicted class=B1  expected loss=0.7083333  P(node) =0.0012
##     class counts:     7     7     3     6     1
##    probabilities: 0.292 0.292 0.125 0.250 0.042 
##   left son=127386 (14 obs) right son=127387 (10 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=1.9714290, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8333333, (0 missing)
##       reimbursement2008 < 5315   to the left,  improve=0.7555556, (0 missing)
##       age               < 67.5   to the right, improve=0.6250000, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5594406, (0 missing)
##   Surrogate splits:
##       age               < 75.5   to the left,  agree=0.708, adj=0.3, (0 split)
##       cancer            < 0.5    to the left,  agree=0.708, adj=0.3, (0 split)
##       reimbursement2008 < 5035   to the right, agree=0.667, adj=0.2, (0 split)
##       copd              < 0.5    to the right, agree=0.625, adj=0.1, (0 split)
## 
## Node number 64424: 14 observations
##   predicted class=B2  expected loss=0.1428571  P(node) =0.0007
##     class counts:     1    12     1     0     0
##    probabilities: 0.071 0.857 0.071 0.000 0.000 
## 
## Node number 64425: 38 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5789474  P(node) =0.0019
##     class counts:     7    16     9     5     1
##    probabilities: 0.184 0.421 0.237 0.132 0.026 
##   left son=128850 (25 obs) right son=128851 (13 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the right, improve=1.7548180, (0 missing)
##       reimbursement2008 < 12915  to the right, improve=1.5553310, (0 missing)
##       copd              < 0.5    to the left,  improve=0.7455870, (0 missing)
##       depression        < 0.5    to the right, improve=0.6704998, (0 missing)
##       age               < 85     to the right, improve=0.5436090, (0 missing)
## 
## Node number 64426: 37 observations
##   predicted class=B2  expected loss=0.4594595  P(node) =0.00185
##     class counts:     3    20    10     4     0
##    probabilities: 0.081 0.541 0.270 0.108 0.000 
## 
## Node number 64427: 41 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5853659  P(node) =0.00205
##     class counts:     2    17    16     5     1
##    probabilities: 0.049 0.415 0.390 0.122 0.024 
##   left son=128854 (34 obs) right son=128855 (7 obs)
##   Primary splits:
##       reimbursement2008 < 10175  to the left,  improve=0.9840131, (0 missing)
##       age               < 64.5   to the left,  improve=0.7571224, (0 missing)
##       stroke            < 0.5    to the right, improve=0.6917388, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.3468219, (0 missing)
##       copd              < 0.5    to the left,  improve=0.2795313, (0 missing)
## 
## Node number 65130: 22 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.6363636  P(node) =0.0011
##     class counts:     6     8     3     5     0
##    probabilities: 0.273 0.364 0.136 0.227 0.000 
##   left son=130260 (10 obs) right son=130261 (12 obs)
##   Primary splits:
##       reimbursement2008 < 17685  to the right, improve=0.7424242, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7305195, (0 missing)
##       age               < 86.5   to the right, improve=0.5415695, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3706294, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.727, adj=0.4, (0 split)
##       age        < 87.5   to the left,  agree=0.591, adj=0.1, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.591, adj=0.1, (0 split)
## 
## Node number 65131: 7 observations
##   predicted class=B4  expected loss=0.4285714  P(node) =0.00035
##     class counts:     1     0     1     4     1
##    probabilities: 0.143 0.000 0.143 0.571 0.143 
## 
## Node number 65506: 72 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6666667  P(node) =0.0036
##     class counts:    11    24    14    20     3
##    probabilities: 0.153 0.333 0.194 0.278 0.042 
##   left son=131012 (65 obs) right son=131013 (7 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the right, improve=1.701282, (0 missing)
##       reimbursement2008 < 55300  to the right, improve=1.679167, (0 missing)
##       bucket2008        < 4.5    to the right, improve=1.679167, (0 missing)
##       age               < 72.5   to the left,  improve=1.502101, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.261148, (0 missing)
## 
## Node number 65507: 60 observations,    complexity param=0.0004563432
##   predicted class=B3  expected loss=0.6333333  P(node) =0.003
##     class counts:     3    19    22    14     2
##    probabilities: 0.050 0.317 0.367 0.233 0.033 
##   left son=131014 (38 obs) right son=131015 (22 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=1.7395530, (0 missing)
##       reimbursement2008 < 44435  to the left,  improve=1.6555560, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.1000000, (0 missing)
##       age               < 59.5   to the right, improve=0.5781297, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4219048, (0 missing)
##   Surrogate splits:
##       age < 66.5   to the left,  agree=0.65, adj=0.045, (0 split)
## 
## Node number 94396: 38 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3684211  P(node) =0.0019
##     class counts:    24    11     2     1     0
##    probabilities: 0.632 0.289 0.053 0.026 0.000 
##   left son=188792 (18 obs) right son=188793 (20 obs)
##   Primary splits:
##       reimbursement2008 < 975    to the right, improve=1.00409400, (0 missing)
##       age               < 71.5   to the left,  improve=0.83583960, (0 missing)
##       depression        < 0.5    to the right, improve=0.22677660, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.07803993, (0 missing)
##   Surrogate splits:
##       age        < 68.5   to the left,  agree=0.658, adj=0.278, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.605, adj=0.167, (0 split)
##       arthritis  < 0.5    to the right, agree=0.553, adj=0.056, (0 split)
##       depression < 0.5    to the right, agree=0.553, adj=0.056, (0 split)
## 
## Node number 94397: 10 observations
##   predicted class=B1  expected loss=0.2  P(node) =0.0005
##     class counts:     8     0     1     1     0
##    probabilities: 0.800 0.000 0.100 0.100 0.000 
## 
## Node number 106724: 9 observations
##   predicted class=B1  expected loss=0.2222222  P(node) =0.00045
##     class counts:     7     2     0     0     0
##    probabilities: 0.778 0.222 0.000 0.000 0.000 
## 
## Node number 106725: 11 observations
##   predicted class=B2  expected loss=0.4545455  P(node) =0.00055
##     class counts:     5     6     0     0     0
##    probabilities: 0.455 0.545 0.000 0.000 0.000 
## 
## Node number 107036: 17 observations
##   predicted class=B1  expected loss=0.2941176  P(node) =0.00085
##     class counts:    12     2     3     0     0
##    probabilities: 0.706 0.118 0.176 0.000 0.000 
## 
## Node number 107037: 12 observations
##   predicted class=B2  expected loss=0.5833333  P(node) =0.0006
##     class counts:     4     5     2     1     0
##    probabilities: 0.333 0.417 0.167 0.083 0.000 
## 
## Node number 107038: 30 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5666667  P(node) =0.0015
##     class counts:    13    11     2     4     0
##    probabilities: 0.433 0.367 0.067 0.133 0.000 
##   left son=214076 (12 obs) right son=214077 (18 obs)
##   Primary splits:
##       reimbursement2008 < 1910   to the right, improve=2.00000000, (0 missing)
##       age               < 71.5   to the left,  improve=0.27777780, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.07660455, (0 missing)
##   Surrogate splits:
##       arthritis < 0.5    to the right, agree=0.733, adj=0.333, (0 split)
##       age       < 72.5   to the right, agree=0.667, adj=0.167, (0 split)
##       copd      < 0.5    to the right, agree=0.633, adj=0.083, (0 split)
## 
## Node number 107039: 9 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.00045
##     class counts:     1     5     1     2     0
##    probabilities: 0.111 0.556 0.111 0.222 0.000 
## 
## Node number 107264: 18 observations
##   predicted class=B1  expected loss=0.3888889  P(node) =0.0009
##     class counts:    11     6     0     1     0
##    probabilities: 0.611 0.333 0.000 0.056 0.000 
## 
## Node number 107265: 15 observations
##   predicted class=B2  expected loss=0.4666667  P(node) =0.00075
##     class counts:     6     8     1     0     0
##    probabilities: 0.400 0.533 0.067 0.000 0.000 
## 
## Node number 122990: 10 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0005
##     class counts:     5     2     3     0     0
##    probabilities: 0.500 0.200 0.300 0.000 0.000 
## 
## Node number 122991: 13 observations
##   predicted class=B3  expected loss=0.3846154  P(node) =0.00065
##     class counts:     3     2     8     0     0
##    probabilities: 0.231 0.154 0.615 0.000 0.000 
## 
## Node number 123410: 13 observations
##   predicted class=B1  expected loss=0.3076923  P(node) =0.00065
##     class counts:     9     2     2     0     0
##    probabilities: 0.692 0.154 0.154 0.000 0.000 
## 
## Node number 123411: 15 observations
##   predicted class=B2  expected loss=0.2666667  P(node) =0.00075
##     class counts:     3    11     1     0     0
##    probabilities: 0.200 0.733 0.067 0.000 0.000 
## 
## Node number 126628: 13 observations
##   predicted class=B2  expected loss=0.1538462  P(node) =0.00065
##     class counts:     1    11     1     0     0
##    probabilities: 0.077 0.846 0.077 0.000 0.000 
## 
## Node number 126629: 23 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5652174  P(node) =0.00115
##     class counts:     7    10     4     2     0
##    probabilities: 0.304 0.435 0.174 0.087 0.000 
##   left son=253258 (7 obs) right son=253259 (16 obs)
##   Primary splits:
##       reimbursement2008 < 5980   to the left,  improve=1.2771740, (0 missing)
##       age               < 74.5   to the left,  improve=0.9688406, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.5309618, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.2279315, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.783, adj=0.286, (0 split)
## 
## Node number 126644: 9 observations
##   predicted class=B1  expected loss=0.6666667  P(node) =0.00045
##     class counts:     3     2     3     1     0
##    probabilities: 0.333 0.222 0.333 0.111 0.000 
## 
## Node number 126645: 12 observations
##   predicted class=B2  expected loss=0.3333333  P(node) =0.0006
##     class counts:     1     8     2     1     0
##    probabilities: 0.083 0.667 0.167 0.083 0.000 
## 
## Node number 127180: 39 observations,    complexity param=0.0002738059
##   predicted class=B1  expected loss=0.6410256  P(node) =0.00195
##     class counts:    14    14     7     4     0
##    probabilities: 0.359 0.359 0.179 0.103 0.000 
##   left son=254360 (8 obs) right son=254361 (31 obs)
##   Primary splits:
##       reimbursement2008 < 9355   to the right, improve=2.2578580, (0 missing)
##       age               < 71.5   to the left,  improve=1.1925780, (0 missing)
##       depression        < 0.5    to the right, improve=1.1320510, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9857550, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8153846, (0 missing)
## 
## Node number 127181: 26 observations
##   predicted class=B2  expected loss=0.3461538  P(node) =0.0013
##     class counts:     2    17     3     3     1
##    probabilities: 0.077 0.654 0.115 0.115 0.038 
## 
## Node number 127182: 28 observations,    complexity param=0.0002738059
##   predicted class=B4  expected loss=0.6428571  P(node) =0.0014
##     class counts:     9     6     2    10     1
##    probabilities: 0.321 0.214 0.071 0.357 0.036 
##   left son=254364 (7 obs) right son=254365 (21 obs)
##   Primary splits:
##       reimbursement2008 < 10940  to the left,  improve=1.880952, (0 missing)
##       age               < 66.5   to the right, improve=1.121429, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.715873, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.515873, (0 missing)
##       depression        < 0.5    to the left,  improve=0.500000, (0 missing)
## 
## Node number 127183: 34 observations,    complexity param=0.0002738059
##   predicted class=B2  expected loss=0.5588235  P(node) =0.0017
##     class counts:     5    15     4     8     2
##    probabilities: 0.147 0.441 0.118 0.235 0.059 
##   left son=254366 (25 obs) right son=254367 (9 obs)
##   Primary splits:
##       age               < 65.5   to the left,  improve=1.9009150, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.7219250, (0 missing)
##       reimbursement2008 < 8370   to the right, improve=1.2050420, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.5834881, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5050420, (0 missing)
## 
## Node number 127378: 14 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.0007
##     class counts:     8     3     1     2     0
##    probabilities: 0.571 0.214 0.071 0.143 0.000 
## 
## Node number 127379: 26 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.6923077  P(node) =0.0013
##     class counts:     6     6     8     4     2
##    probabilities: 0.231 0.231 0.308 0.154 0.077 
##   left son=254758 (19 obs) right son=254759 (7 obs)
##   Primary splits:
##       reimbursement2008 < 3885   to the left,  improve=1.2631580, (0 missing)
##       age               < 75.5   to the right, improve=0.8969697, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6388889, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.4967320, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4444444, (0 missing)
## 
## Node number 127386: 14 observations
##   predicted class=B2  expected loss=0.5714286  P(node) =0.0007
##     class counts:     5     6     1     1     1
##    probabilities: 0.357 0.429 0.071 0.071 0.071 
## 
## Node number 127387: 10 observations
##   predicted class=B4  expected loss=0.5  P(node) =0.0005
##     class counts:     2     1     2     5     0
##    probabilities: 0.200 0.100 0.200 0.500 0.000 
## 
## Node number 128850: 25 observations
##   predicted class=B2  expected loss=0.48  P(node) =0.00125
##     class counts:     5    13     3     3     1
##    probabilities: 0.200 0.520 0.120 0.120 0.040 
## 
## Node number 128851: 13 observations
##   predicted class=B3  expected loss=0.5384615  P(node) =0.00065
##     class counts:     2     3     6     2     0
##    probabilities: 0.154 0.231 0.462 0.154 0.000 
## 
## Node number 128854: 34 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5294118  P(node) =0.0017
##     class counts:     1    16    12     4     1
##    probabilities: 0.029 0.471 0.353 0.118 0.029 
##   left son=257708 (7 obs) right son=257709 (27 obs)
##   Primary splits:
##       reimbursement2008 < 9480   to the right, improve=0.9333956, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7647059, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5044172, (0 missing)
##       stroke            < 0.5    to the right, improve=0.4174208, (0 missing)
##       age               < 77.5   to the left,  improve=0.4003268, (0 missing)
## 
## Node number 128855: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     1     1     4     1     0
##    probabilities: 0.143 0.143 0.571 0.143 0.000 
## 
## Node number 130260: 10 observations
##   predicted class=B1  expected loss=0.6  P(node) =0.0005
##     class counts:     4     3     2     1     0
##    probabilities: 0.400 0.300 0.200 0.100 0.000 
## 
## Node number 130261: 12 observations
##   predicted class=B2  expected loss=0.5833333  P(node) =0.0006
##     class counts:     2     5     1     4     0
##    probabilities: 0.167 0.417 0.083 0.333 0.000 
## 
## Node number 131012: 65 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6307692  P(node) =0.00325
##     class counts:     9    24    13    16     3
##    probabilities: 0.138 0.369 0.200 0.246 0.046 
##   left son=262024 (46 obs) right son=262025 (19 obs)
##   Primary splits:
##       age               < 72.5   to the right, improve=1.560922, (0 missing)
##       reimbursement2008 < 55990  to the right, improve=1.281022, (0 missing)
##       bucket2008        < 4.5    to the right, improve=1.276687, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.268239, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.084950, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 69985  to the left,  agree=0.723, adj=0.053, (0 split)
## 
## Node number 131013: 7 observations
##   predicted class=B4  expected loss=0.4285714  P(node) =0.00035
##     class counts:     2     0     1     4     0
##    probabilities: 0.286 0.000 0.143 0.571 0.000 
## 
## Node number 131014: 38 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.5263158  P(node) =0.0019
##     class counts:     2    10    18     7     1
##    probabilities: 0.053 0.263 0.474 0.184 0.026 
##   left son=262028 (16 obs) right son=262029 (22 obs)
##   Primary splits:
##       reimbursement2008 < 44435  to the left,  improve=1.4210530, (0 missing)
##       depression        < 0.5    to the right, improve=1.1577470, (0 missing)
##       age               < 44     to the left,  improve=0.8219743, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.6702834, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5996241, (0 missing)
##   Surrogate splits:
##       bucket2008 < 4.5    to the left,  agree=0.789, adj=0.500, (0 split)
##       copd       < 0.5    to the left,  agree=0.737, adj=0.375, (0 split)
##       cancer     < 0.5    to the right, agree=0.658, adj=0.188, (0 split)
##       age        < 49     to the left,  agree=0.632, adj=0.125, (0 split)
## 
## Node number 131015: 22 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5909091  P(node) =0.0011
##     class counts:     1     9     4     7     1
##    probabilities: 0.045 0.409 0.182 0.318 0.045 
##   left son=262030 (8 obs) right son=262031 (14 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=1.2012990, (0 missing)
##       age               < 61     to the right, improve=0.8966589, (0 missing)
##       reimbursement2008 < 53960  to the right, improve=0.8060606, (0 missing)
##       bucket2008        < 4.5    to the right, improve=0.7272727, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.1060606, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 75515  to the right, agree=0.727, adj=0.250, (0 split)
##       age               < 61     to the right, agree=0.682, adj=0.125, (0 split)
## 
## Node number 188792: 18 observations
##   predicted class=B1  expected loss=0.2222222  P(node) =0.0009
##     class counts:    14     4     0     0     0
##    probabilities: 0.778 0.222 0.000 0.000 0.000 
## 
## Node number 188793: 20 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.5  P(node) =0.001
##     class counts:    10     7     2     1     0
##    probabilities: 0.500 0.350 0.100 0.050 0.000 
##   left son=377586 (12 obs) right son=377587 (8 obs)
##   Primary splits:
##       age               < 71.5   to the left,  improve=1.883333, (0 missing)
##       reimbursement2008 < 915    to the left,  improve=1.451515, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.256044, (0 missing)
##   Surrogate splits:
##       arthritis         < 0.5    to the left,  agree=0.7, adj=0.25, (0 split)
##       reimbursement2008 < 930    to the left,  agree=0.7, adj=0.25, (0 split)
## 
## Node number 214076: 12 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0006
##     class counts:     8     2     0     2     0
##    probabilities: 0.667 0.167 0.000 0.167 0.000 
## 
## Node number 214077: 18 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0009
##     class counts:     5     9     2     2     0
##    probabilities: 0.278 0.500 0.111 0.111 0.000 
## 
## Node number 253258: 7 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.00035
##     class counts:     4     2     0     1     0
##    probabilities: 0.571 0.286 0.000 0.143 0.000 
## 
## Node number 253259: 16 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0008
##     class counts:     3     8     4     1     0
##    probabilities: 0.188 0.500 0.250 0.062 0.000 
## 
## Node number 254360: 8 observations
##   predicted class=B1  expected loss=0.375  P(node) =0.0004
##     class counts:     5     0     1     2     0
##    probabilities: 0.625 0.000 0.125 0.250 0.000 
## 
## Node number 254361: 31 observations,    complexity param=0.0002738059
##   predicted class=B2  expected loss=0.5483871  P(node) =0.00155
##     class counts:     9    14     6     2     0
##    probabilities: 0.290 0.452 0.194 0.065 0.000 
##   left son=508722 (9 obs) right son=508723 (22 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=1.6226780, (0 missing)
##       age               < 71.5   to the left,  improve=1.3876390, (0 missing)
##       reimbursement2008 < 7390   to the right, improve=0.9646697, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.8980031, (0 missing)
##       copd              < 0.5    to the right, improve=0.8980031, (0 missing)
## 
## Node number 254364: 7 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.00035
##     class counts:     4     0     2     1     0
##    probabilities: 0.571 0.000 0.286 0.143 0.000 
## 
## Node number 254365: 21 observations,    complexity param=0.0001521144
##   predicted class=B4  expected loss=0.5714286  P(node) =0.00105
##     class counts:     5     6     0     9     1
##    probabilities: 0.238 0.286 0.000 0.429 0.048 
##   left son=508730 (13 obs) right son=508731 (8 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=0.8635531, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6995671, (0 missing)
##       age               < 65.5   to the right, improve=0.5943223, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3571429, (0 missing)
##       reimbursement2008 < 12015  to the right, improve=0.3250916, (0 missing)
##   Surrogate splits:
##       copd              < 0.5    to the left,  agree=0.762, adj=0.375, (0 split)
##       age               < 49     to the right, agree=0.714, adj=0.250, (0 split)
##       reimbursement2008 < 14250  to the left,  agree=0.714, adj=0.250, (0 split)
##       cancer            < 0.5    to the left,  agree=0.667, adj=0.125, (0 split)
## 
## Node number 254366: 25 observations
##   predicted class=B2  expected loss=0.48  P(node) =0.00125
##     class counts:     4    13     3     3     2
##    probabilities: 0.160 0.520 0.120 0.120 0.080 
## 
## Node number 254367: 9 observations
##   predicted class=B4  expected loss=0.4444444  P(node) =0.00045
##     class counts:     1     2     1     5     0
##    probabilities: 0.111 0.222 0.111 0.556 0.000 
## 
## Node number 254758: 19 observations
##   predicted class=B1  expected loss=0.6842105  P(node) =0.00095
##     class counts:     6     4     4     3     2
##    probabilities: 0.316 0.211 0.211 0.158 0.105 
## 
## Node number 254759: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     0     2     4     1     0
##    probabilities: 0.000 0.286 0.571 0.143 0.000 
## 
## Node number 257708: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     0     5     1     1     0
##    probabilities: 0.000 0.714 0.143 0.143 0.000 
## 
## Node number 257709: 27 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5925926  P(node) =0.00135
##     class counts:     1    11    11     3     1
##    probabilities: 0.037 0.407 0.407 0.111 0.037 
##   left son=515418 (19 obs) right son=515419 (8 obs)
##   Primary splits:
##       reimbursement2008 < 9020   to the left,  improve=1.7875240, (0 missing)
##       age               < 70.5   to the left,  improve=0.8518519, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8274318, (0 missing)
##       stroke            < 0.5    to the right, improve=0.4010582, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3909933, (0 missing)
## 
## Node number 262024: 46 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5869565  P(node) =0.0023
##     class counts:     5    19    11     8     3
##    probabilities: 0.109 0.413 0.239 0.174 0.065 
##   left son=524048 (25 obs) right son=524049 (21 obs)
##   Primary splits:
##       reimbursement2008 < 52775  to the right, improve=1.6160660, (0 missing)
##       depression        < 0.5    to the right, improve=1.0500350, (0 missing)
##       bucket2008        < 4.5    to the right, improve=1.0446380, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9895186, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.8413043, (0 missing)
##   Surrogate splits:
##       bucket2008 < 4.5    to the right, agree=0.913, adj=0.810, (0 split)
##       arthritis  < 0.5    to the left,  agree=0.630, adj=0.190, (0 split)
##       depression < 0.5    to the right, agree=0.630, adj=0.190, (0 split)
##       cancer     < 0.5    to the left,  agree=0.587, adj=0.095, (0 split)
##       copd       < 0.5    to the right, agree=0.587, adj=0.095, (0 split)
## 
## Node number 262025: 19 observations
##   predicted class=B4  expected loss=0.5789474  P(node) =0.00095
##     class counts:     4     5     2     8     0
##    probabilities: 0.211 0.263 0.105 0.421 0.000 
## 
## Node number 262028: 16 observations
##   predicted class=B3  expected loss=0.375  P(node) =0.0008
##     class counts:     2     2    10     2     0
##    probabilities: 0.125 0.125 0.625 0.125 0.000 
## 
## Node number 262029: 22 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.6363636  P(node) =0.0011
##     class counts:     0     8     8     5     1
##    probabilities: 0.000 0.364 0.364 0.227 0.045 
##   left son=524058 (12 obs) right son=524059 (10 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=1.5666670, (0 missing)
##       reimbursement2008 < 66505  to the right, improve=1.0000000, (0 missing)
##       age               < 58.5   to the left,  improve=0.9642857, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.6761905, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.4358974, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 67825  to the left,  agree=0.773, adj=0.5, (0 split)
##       age               < 66.5   to the left,  agree=0.682, adj=0.3, (0 split)
##       alzheimers        < 0.5    to the right, agree=0.682, adj=0.3, (0 split)
##       arthritis         < 0.5    to the right, agree=0.591, adj=0.1, (0 split)
##       copd              < 0.5    to the right, agree=0.591, adj=0.1, (0 split)
## 
## Node number 262030: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     1     5     1     1     0
##    probabilities: 0.125 0.625 0.125 0.125 0.000 
## 
## Node number 262031: 14 observations
##   predicted class=B4  expected loss=0.5714286  P(node) =0.0007
##     class counts:     0     4     3     6     1
##    probabilities: 0.000 0.286 0.214 0.429 0.071 
## 
## Node number 377586: 12 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0006
##     class counts:     8     2     1     1     0
##    probabilities: 0.667 0.167 0.083 0.083 0.000 
## 
## Node number 377587: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     2     5     1     0     0
##    probabilities: 0.250 0.625 0.125 0.000 0.000 
## 
## Node number 508722: 9 observations
##   predicted class=B1  expected loss=0.4444444  P(node) =0.00045
##     class counts:     5     2     2     0     0
##    probabilities: 0.556 0.222 0.222 0.000 0.000 
## 
## Node number 508723: 22 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4545455  P(node) =0.0011
##     class counts:     4    12     4     2     0
##    probabilities: 0.182 0.545 0.182 0.091 0.000 
##   left son=1017446 (12 obs) right son=1017447 (10 obs)
##   Primary splits:
##       age               < 71.5   to the left,  improve=1.9848480, (0 missing)
##       reimbursement2008 < 7425   to the right, improve=1.2086580, (0 missing)
##       depression        < 0.5    to the right, improve=1.1002330, (0 missing)
##       copd              < 0.5    to the right, improve=0.9967532, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.6753247, (0 missing)
##   Surrogate splits:
##       depression        < 0.5    to the right, agree=0.682, adj=0.3, (0 split)
##       copd              < 0.5    to the right, agree=0.636, adj=0.2, (0 split)
##       ihd               < 0.5    to the right, agree=0.636, adj=0.2, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.636, adj=0.2, (0 split)
##       reimbursement2008 < 7010   to the right, agree=0.636, adj=0.2, (0 split)
## 
## Node number 508730: 13 observations
##   predicted class=B2  expected loss=0.6153846  P(node) =0.00065
##     class counts:     3     5     0     4     1
##    probabilities: 0.231 0.385 0.000 0.308 0.077 
## 
## Node number 508731: 8 observations
##   predicted class=B4  expected loss=0.375  P(node) =0.0004
##     class counts:     2     1     0     5     0
##    probabilities: 0.250 0.125 0.000 0.625 0.000 
## 
## Node number 515418: 19 observations
##   predicted class=B2  expected loss=0.5263158  P(node) =0.00095
##     class counts:     1     9     5     3     1
##    probabilities: 0.053 0.474 0.263 0.158 0.053 
## 
## Node number 515419: 8 observations
##   predicted class=B3  expected loss=0.25  P(node) =0.0004
##     class counts:     0     2     6     0     0
##    probabilities: 0.000 0.250 0.750 0.000 0.000 
## 
## Node number 524048: 25 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.64  P(node) =0.00125
##     class counts:     4     9     9     2     1
##    probabilities: 0.160 0.360 0.360 0.080 0.040 
##   left son=1048096 (11 obs) right son=1048097 (14 obs)
##   Primary splits:
##       reimbursement2008 < 59785  to the right, improve=2.4722080, (0 missing)
##       age               < 76.5   to the right, improve=0.7825641, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.5466667, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2682353, (0 missing)
##       depression        < 0.5    to the right, improve=0.1561905, (0 missing)
##   Surrogate splits:
##       age        < 79.5   to the right, agree=0.64, adj=0.182, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.64, adj=0.182, (0 split)
##       cancer     < 0.5    to the right, agree=0.64, adj=0.182, (0 split)
##       depression < 0.5    to the left,  agree=0.60, adj=0.091, (0 split)
##       bucket2008 < 4.5    to the right, agree=0.60, adj=0.091, (0 split)
## 
## Node number 524049: 21 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5238095  P(node) =0.00105
##     class counts:     1    10     2     6     2
##    probabilities: 0.048 0.476 0.095 0.286 0.095 
##   left son=1048098 (7 obs) right son=1048099 (14 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=1.9523810, (0 missing)
##       depression        < 0.5    to the left,  improve=1.1316020, (0 missing)
##       reimbursement2008 < 41140  to the left,  improve=1.0760070, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.4043290, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2875458, (0 missing)
##   Surrogate splits:
##       age               < 78.5   to the right, agree=0.810, adj=0.429, (0 split)
##       reimbursement2008 < 40060  to the left,  agree=0.762, adj=0.286, (0 split)
## 
## Node number 524058: 12 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0006
##     class counts:     0     6     2     3     1
##    probabilities: 0.000 0.500 0.167 0.250 0.083 
## 
## Node number 524059: 10 observations
##   predicted class=B3  expected loss=0.4  P(node) =0.0005
##     class counts:     0     2     6     2     0
##    probabilities: 0.000 0.200 0.600 0.200 0.000 
## 
## Node number 1017446: 12 observations
##   predicted class=B2  expected loss=0.25  P(node) =0.0006
##     class counts:     2     9     0     1     0
##    probabilities: 0.167 0.750 0.000 0.083 0.000 
## 
## Node number 1017447: 10 observations
##   predicted class=B3  expected loss=0.6  P(node) =0.0005
##     class counts:     2     3     4     1     0
##    probabilities: 0.200 0.300 0.400 0.100 0.000 
## 
## Node number 1048096: 11 observations
##   predicted class=B1  expected loss=0.6363636  P(node) =0.00055
##     class counts:     4     4     1     2     0
##    probabilities: 0.364 0.364 0.091 0.182 0.000 
## 
## Node number 1048097: 14 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.0007
##     class counts:     0     5     8     0     1
##    probabilities: 0.000 0.357 0.571 0.000 0.071 
## 
## Node number 1048098: 7 observations
##   predicted class=B2  expected loss=0.1428571  P(node) =0.00035
##     class counts:     0     6     0     1     0
##    probabilities: 0.000 0.857 0.000 0.143 0.000 
## 
## Node number 1048099: 14 observations
##   predicted class=B4  expected loss=0.6428571  P(node) =0.0007
##     class counts:     1     4     2     5     2
##    probabilities: 0.071 0.286 0.143 0.357 0.143 
## 
## n= 20000 
## 
## node), split, n, loss, yval, (yprob)
##       * denotes terminal node
## 
##       1) root 20000 6574 B1 (0.67 0.19 0.089 0.043 0.0057)  
##         2) reimbursement2008< 1565 12142 1549 B1 (0.87 0.077 0.036 0.014 0.0016)  
##           4) reimbursement2008< 195 6456  205 B1 (0.97 0.017 0.011 0.0039 0.00046) *
##           5) reimbursement2008>=195 5686 1344 B1 (0.76 0.15 0.064 0.024 0.0028)  
##            10) reimbursement2008< 685 2374  402 B1 (0.83 0.1 0.052 0.015 0.0021)  
##              20) diabetes< 0.5 1860  289 B1 (0.84 0.095 0.046 0.012 0.0022)  
##                40) age< 89.5 1774  266 B1 (0.85 0.093 0.042 0.013 0.0017)  
##                  80) age>=29.5 1764  262 B1 (0.85 0.092 0.043 0.012 0.0017)  
##                   160) osteoporosis< 0.5 1586  227 B1 (0.86 0.086 0.043 0.012 0.0019)  
##                     320) age< 71.5 756   92 B1 (0.88 0.075 0.036 0.0093 0.0013) *
##                     321) age>=71.5 830  135 B1 (0.84 0.096 0.049 0.014 0.0024)  
##                       642) reimbursement2008< 665 801  127 B1 (0.84 0.091 0.05 0.015 0.0025)  
##                        1284) reimbursement2008< 245 94   10 B1 (0.89 0.053 0.043 0.011 0) *
##                        1285) reimbursement2008>=245 707  117 B1 (0.83 0.096 0.051 0.016 0.0028)  
##                          2570) reimbursement2008>=495 277   38 B1 (0.86 0.076 0.036 0.025 0) *
##                          2571) reimbursement2008< 495 430   79 B1 (0.82 0.11 0.06 0.0093 0.0047)  
##                            5142) reimbursement2008< 475 398   70 B1 (0.82 0.098 0.065 0.0075 0.005)  
##                             10284) ihd< 0.5 321   52 B1 (0.84 0.087 0.059 0.0093 0.0062) *
##                             10285) ihd>=0.5 77   18 B1 (0.77 0.14 0.091 0 0)  
##                               20570) age< 86.5 70   12 B1 (0.83 0.1 0.071 0 0) *
##                               20571) age>=86.5 7    3 B2 (0.14 0.57 0.29 0 0) *
##                            5143) reimbursement2008>=475 32    9 B1 (0.72 0.25 0 0.031 0)  
##                             10286) age>=83.5 10    1 B1 (0.9 0.1 0 0 0) *
##                             10287) age< 83.5 22    8 B1 (0.64 0.32 0 0.045 0)  
##                               20574) age< 78.5 14    2 B1 (0.86 0.14 0 0 0) *
##                               20575) age>=78.5 8    3 B2 (0.25 0.62 0 0.12 0) *
##                       643) reimbursement2008>=665 29    8 B1 (0.72 0.24 0.034 0 0) *
##                   161) osteoporosis>=0.5 178   35 B1 (0.8 0.14 0.039 0.017 0)  
##                     322) reimbursement2008>=225 171   31 B1 (0.82 0.12 0.041 0.018 0) *
##                     323) reimbursement2008< 225 7    3 B2 (0.43 0.57 0 0 0) *
##                  81) age< 29.5 10    4 B1 (0.6 0.3 0 0.1 0) *
##                41) age>=89.5 86   23 B1 (0.73 0.13 0.13 0 0.012) *
##              21) diabetes>=0.5 514  113 B1 (0.78 0.12 0.072 0.023 0.0019)  
##                42) reimbursement2008< 425 173   28 B1 (0.84 0.075 0.064 0.023 0)  
##                  84) age>=64.5 147   18 B1 (0.88 0.061 0.048 0.014 0) *
##                  85) age< 64.5 26   10 B1 (0.62 0.15 0.15 0.077 0)  
##                   170) reimbursement2008>=250 19    5 B1 (0.74 0.11 0.053 0.11 0) *
##                   171) reimbursement2008< 250 7    4 B3 (0.29 0.29 0.43 0 0) *
##                43) reimbursement2008>=425 341   85 B1 (0.75 0.15 0.076 0.023 0.0029) *
##            11) reimbursement2008>=685 3312  942 B1 (0.72 0.18 0.073 0.031 0.0033)  
##              22) ihd< 0.5 1722  424 B1 (0.75 0.15 0.062 0.03 0.0029)  
##                44) reimbursement2008< 1085 951  209 B1 (0.78 0.14 0.05 0.027 0.0032)  
##                  88) alzheimers< 0.5 811  169 B1 (0.79 0.13 0.047 0.03 0.0025)  
##                   176) diabetes< 0.5 544  105 B1 (0.81 0.11 0.048 0.031 0.0037)  
##                     352) reimbursement2008< 905 338   59 B1 (0.83 0.086 0.059 0.024 0.0059) *
##                     353) reimbursement2008>=905 206   46 B1 (0.78 0.15 0.029 0.044 0)  
##                       706) reimbursement2008>=955 149   25 B1 (0.83 0.12 0.02 0.027 0) *
##                       707) reimbursement2008< 955 57   21 B1 (0.63 0.23 0.053 0.088 0)  
##                        1414) age< 83.5 43   12 B1 (0.72 0.14 0.07 0.07 0) *
##                        1415) age>=83.5 14    7 B2 (0.36 0.5 0 0.14 0) *
##                   177) diabetes>=0.5 267   64 B1 (0.76 0.17 0.045 0.026 0)  
##                     354) reimbursement2008>=795 182   38 B1 (0.79 0.13 0.049 0.027 0) *
##                     355) reimbursement2008< 795 85   26 B1 (0.69 0.25 0.035 0.024 0)  
##                       710) reimbursement2008< 785 76   21 B1 (0.72 0.21 0.039 0.026 0)  
##                        1420) age>=81 9    1 B1 (0.89 0 0 0.11 0) *
##                        1421) age< 81 67   20 B1 (0.7 0.24 0.045 0.015 0)  
##                          2842) age< 78.5 60   16 B1 (0.73 0.2 0.05 0.017 0) *
##                          2843) age>=78.5 7    3 B2 (0.43 0.57 0 0 0) *
##                       711) reimbursement2008>=785 9    4 B2 (0.44 0.56 0 0 0) *
##                  89) alzheimers>=0.5 140   40 B1 (0.71 0.19 0.071 0.014 0.0071)  
##                   178) age< 91.5 133   35 B1 (0.74 0.18 0.068 0.0075 0.0075) *
##                   179) age>=91.5 7    4 B2 (0.29 0.43 0.14 0.14 0) *
##                45) reimbursement2008>=1085 771  215 B1 (0.72 0.17 0.077 0.032 0.0026)  
##                  90) stroke< 0.5 758  207 B1 (0.73 0.17 0.071 0.033 0.0026)  
##                   180) osteoporosis< 0.5 586  150 B1 (0.74 0.15 0.073 0.032 0)  
##                     360) age>=67.5 449  107 B1 (0.76 0.13 0.08 0.031 0)  
##                       720) reimbursement2008< 1335 283   60 B1 (0.79 0.1 0.078 0.032 0)  
##                        1440) age>=87.5 27    2 B1 (0.93 0.037 0.037 0 0) *
##                        1441) age< 87.5 256   58 B1 (0.77 0.11 0.082 0.035 0)  
##                          2882) age< 80.5 197   38 B1 (0.81 0.091 0.066 0.036 0) *
##                          2883) age>=80.5 59   20 B1 (0.66 0.17 0.14 0.034 0)  
##                            5766) reimbursement2008>=1115 51   15 B1 (0.71 0.12 0.14 0.039 0) *
##                            5767) reimbursement2008< 1115 8    4 B2 (0.38 0.5 0.12 0 0) *
##                       721) reimbursement2008>=1335 166   47 B1 (0.72 0.17 0.084 0.03 0)  
##                        1442) copd< 0.5 158   43 B1 (0.73 0.16 0.082 0.032 0)  
##                          2884) age>=73.5 109   31 B1 (0.72 0.19 0.083 0.0092 0)  
##                            5768) age>=77.5 79   18 B1 (0.77 0.14 0.076 0.013 0) *
##                            5769) age< 77.5 30   13 B1 (0.57 0.33 0.1 0 0)  
##                             11538) arthritis< 0.5 23    8 B1 (0.65 0.22 0.13 0 0) *
##                             11539) arthritis>=0.5 7    2 B2 (0.29 0.71 0 0 0) *
##                          2885) age< 73.5 49   12 B1 (0.76 0.082 0.082 0.082 0) *
##                        1443) copd>=0.5 8    4 B1 (0.5 0.38 0.12 0 0) *
##                     361) age< 67.5 137   43 B1 (0.69 0.23 0.051 0.036 0)  
##                       722) reimbursement2008>=1345 50   13 B1 (0.74 0.14 0.08 0.04 0) *
##                       723) reimbursement2008< 1345 87   30 B1 (0.66 0.28 0.034 0.034 0)  
##                        1446) reimbursement2008< 1235 52   15 B1 (0.71 0.19 0.038 0.058 0)  
##                          2892) reimbursement2008>=1155 32    6 B1 (0.81 0.12 0.031 0.031 0) *
##                          2893) reimbursement2008< 1155 20    9 B1 (0.55 0.3 0.05 0.1 0)  
##                            5786) reimbursement2008< 1115 9    2 B1 (0.78 0.11 0 0.11 0) *
##                            5787) reimbursement2008>=1115 11    6 B2 (0.36 0.45 0.091 0.091 0) *
##                        1447) reimbursement2008>=1235 35   15 B1 (0.57 0.4 0.029 0 0)  
##                          2894) diabetes>=0.5 15    4 B1 (0.73 0.2 0.067 0 0) *
##                          2895) diabetes< 0.5 20    9 B2 (0.45 0.55 0 0 0)  
##                            5790) reimbursement2008>=1275 11    5 B1 (0.55 0.45 0 0 0) *
##                            5791) reimbursement2008< 1275 9    3 B2 (0.33 0.67 0 0 0) *
##                   181) osteoporosis>=0.5 172   57 B1 (0.67 0.22 0.064 0.035 0.012)  
##                     362) age< 83.5 143   42 B1 (0.71 0.2 0.056 0.028 0.014)  
##                       724) age>=75.5 44    8 B1 (0.82 0.11 0.023 0.023 0.023) *
##                       725) age< 75.5 99   34 B1 (0.66 0.23 0.071 0.03 0.01)  
##                        1450) age< 73.5 88   26 B1 (0.7 0.19 0.057 0.034 0.011) *
##                        1451) age>=73.5 11    5 B2 (0.27 0.55 0.18 0 0) *
##                     363) age>=83.5 29   15 B1 (0.48 0.34 0.1 0.069 0)  
##                       726) diabetes< 0.5 17    6 B1 (0.65 0.24 0.059 0.059 0) *
##                       727) diabetes>=0.5 12    6 B2 (0.25 0.5 0.17 0.083 0) *
##                  91) stroke>=0.5 13    8 B1 (0.38 0.23 0.38 0 0) *
##              23) ihd>=0.5 1590  518 B1 (0.67 0.2 0.084 0.033 0.0038)  
##                46) diabetes< 0.5 771  220 B1 (0.71 0.18 0.078 0.022 0.0052)  
##                  92) kidney< 0.5 713  194 B1 (0.73 0.18 0.072 0.02 0.0056)  
##                   184) age>=39.5 691  184 B1 (0.73 0.17 0.072 0.019 0.0029)  
##                     368) reimbursement2008< 1465 628  161 B1 (0.74 0.17 0.068 0.019 0.0032)  
##                       736) heart.failure< 0.5 455  105 B1 (0.77 0.15 0.057 0.015 0.0044) *
##                       737) heart.failure>=0.5 173   56 B1 (0.68 0.2 0.098 0.029 0)  
##                        1474) reimbursement2008>=820 145   41 B1 (0.72 0.17 0.09 0.021 0)  
##                          2948) age< 51 8    0 B1 (1 0 0 0 0) *
##                          2949) age>=51 137   41 B1 (0.7 0.18 0.095 0.022 0)  
##                            5898) copd>=0.5 10    1 B1 (0.9 0 0.1 0 0) *
##                            5899) copd< 0.5 127   40 B1 (0.69 0.2 0.094 0.024 0)  
##                             11798) reimbursement2008< 875 8    1 B1 (0.88 0 0.12 0 0) *
##                             11799) reimbursement2008>=875 119   39 B1 (0.67 0.21 0.092 0.025 0)  
##                               23598) reimbursement2008>=1125 63   18 B1 (0.71 0.16 0.13 0 0) *
##                               23599) reimbursement2008< 1125 56   21 B1 (0.62 0.27 0.054 0.054 0)  
##                                 47198) age< 80.5 48   16 B1 (0.67 0.23 0.062 0.042 0)  
##                                   94396) age< 74.5 38   14 B1 (0.63 0.29 0.053 0.026 0)  
##                                    188792) reimbursement2008>=975 18    4 B1 (0.78 0.22 0 0 0) *
##                                    188793) reimbursement2008< 975 20   10 B1 (0.5 0.35 0.1 0.05 0)  
##                                      377586) age< 71.5 12    4 B1 (0.67 0.17 0.083 0.083 0) *
##                                      377587) age>=71.5 8    3 B2 (0.25 0.62 0.12 0 0) *
##                                   94397) age>=74.5 10    2 B1 (0.8 0 0.1 0.1 0) *
##                                 47199) age>=80.5 8    4 B2 (0.38 0.5 0 0.12 0) *
##                        1475) reimbursement2008< 820 28   15 B1 (0.46 0.32 0.14 0.071 0)  
##                          2950) age>=78.5 8    2 B1 (0.75 0.12 0 0.12 0) *
##                          2951) age< 78.5 20   12 B2 (0.35 0.4 0.2 0.05 0)  
##                            5902) age< 66.5 7    4 B1 (0.43 0.29 0.29 0 0) *
##                            5903) age>=66.5 13    7 B2 (0.31 0.46 0.15 0.077 0) *
##                     369) reimbursement2008>=1465 63   23 B1 (0.63 0.24 0.11 0.016 0)  
##                       738) reimbursement2008>=1485 52   16 B1 (0.69 0.19 0.096 0.019 0) *
##                       739) reimbursement2008< 1485 11    6 B2 (0.36 0.45 0.18 0 0) *
##                   185) age< 39.5 22   10 B1 (0.55 0.27 0.045 0.045 0.091) *
##                  93) kidney>=0.5 58   26 B1 (0.55 0.24 0.16 0.052 0)  
##                   186) age< 69.5 15    2 B1 (0.87 0 0.13 0 0) *
##                   187) age>=69.5 43   24 B1 (0.44 0.33 0.16 0.07 0)  
##                     374) reimbursement2008< 1355 35   17 B1 (0.51 0.26 0.14 0.086 0)  
##                       748) reimbursement2008>=895 28   12 B1 (0.57 0.25 0.071 0.11 0) *
##                       749) reimbursement2008< 895 7    4 B3 (0.29 0.29 0.43 0 0) *
##                     375) reimbursement2008>=1355 8    3 B2 (0.12 0.62 0.25 0 0) *
##                47) diabetes>=0.5 819  298 B1 (0.64 0.23 0.09 0.044 0.0024)  
##                  94) reimbursement2008< 1155 412  126 B1 (0.69 0.19 0.083 0.029 0.0024)  
##                   188) osteoporosis>=0.5 90   19 B1 (0.79 0.11 0.078 0.022 0) *
##                   189) osteoporosis< 0.5 322  107 B1 (0.67 0.21 0.084 0.031 0.0031)  
##                     378) age>=46.5 310   99 B1 (0.68 0.21 0.077 0.029 0.0032)  
##                       756) reimbursement2008>=835 213   61 B1 (0.71 0.19 0.08 0.014 0.0047)  
##                        1512) age>=79.5 74   17 B1 (0.77 0.12 0.068 0.041 0) *
##                        1513) age< 79.5 139   44 B1 (0.68 0.22 0.086 0 0.0072)  
##                          3026) reimbursement2008>=1105 14    1 B1 (0.93 0.071 0 0 0) *
##                          3027) reimbursement2008< 1105 125   43 B1 (0.66 0.24 0.096 0 0.008)  
##                            6054) arthritis>=0.5 10    1 B1 (0.9 0.1 0 0 0) *
##                            6055) arthritis< 0.5 115   42 B1 (0.63 0.25 0.1 0 0.0087)  
##                             12110) age>=73.5 36   14 B1 (0.61 0.36 0.028 0 0)  
##                               24220) reimbursement2008< 1005 28    9 B1 (0.68 0.29 0.036 0 0) *
##                               24221) reimbursement2008>=1005 8    3 B2 (0.38 0.62 0 0 0) *
##                             12111) age< 73.5 79   28 B1 (0.65 0.2 0.14 0 0.013)  
##                               24222) age< 71.5 65   24 B1 (0.63 0.25 0.11 0 0.015)  
##                                 48444) reimbursement2008< 1075 58   20 B1 (0.66 0.21 0.12 0 0.017) *
##                                 48445) reimbursement2008>=1075 7    3 B2 (0.43 0.57 0 0 0) *
##                               24223) age>=71.5 14    4 B1 (0.71 0 0.29 0 0) *
##                       757) reimbursement2008< 835 97   38 B1 (0.61 0.26 0.072 0.062 0)  
##                        1514) age< 80.5 68   23 B1 (0.66 0.19 0.074 0.074 0)  
##                          3028) kidney>=0.5 9    4 B2 (0.44 0.56 0 0 0) *
##                          3029) kidney< 0.5 59   18 B1 (0.69 0.14 0.085 0.085 0) *
##                        1515) age>=80.5 29   15 B1 (0.48 0.41 0.069 0.034 0)  
##                          3030) age>=83.5 20    9 B1 (0.55 0.35 0.05 0.05 0) *
##                          3031) age< 83.5 9    4 B2 (0.33 0.56 0.11 0 0) *
##                     379) age< 46.5 12    8 B1 (0.33 0.33 0.25 0.083 0) *
##                  95) reimbursement2008>=1155 407  172 B1 (0.58 0.26 0.098 0.059 0.0025)  
##                   190) age< 89.5 382  155 B1 (0.59 0.25 0.094 0.058 0.0026)  
##                     380) reimbursement2008>=1175 352  141 B1 (0.6 0.26 0.085 0.051 0)  
##                       760) depression< 0.5 242   90 B1 (0.63 0.27 0.054 0.05 0) *
##                       761) depression>=0.5 110   51 B1 (0.54 0.25 0.15 0.055 0)  
##                        1522) age< 70.5 54   20 B1 (0.63 0.19 0.11 0.074 0) *
##                        1523) age>=70.5 56   31 B1 (0.45 0.32 0.2 0.036 0)  
##                          3046) age>=76.5 31   14 B1 (0.55 0.16 0.23 0.065 0) *
##                          3047) age< 76.5 25   12 B2 (0.32 0.52 0.16 0 0)  
##                            6094) reimbursement2008< 1435 18    8 B2 (0.44 0.56 0 0 0) *
##                            6095) reimbursement2008>=1435 7    3 B3 (0 0.43 0.57 0 0) *
##                     381) reimbursement2008< 1175 30   14 B1 (0.53 0.1 0.2 0.13 0.033)  
##                       762) age>=70 22    8 B1 (0.64 0.091 0.18 0.045 0.045) *
##                       763) age< 70 8    5 B4 (0.25 0.12 0.25 0.38 0) *
##                   191) age>=89.5 25   14 B2 (0.32 0.44 0.16 0.08 0)  
##                     382) depression>=0.5 7    2 B1 (0.71 0.14 0.14 0 0) *
##                     383) depression< 0.5 18    8 B2 (0.17 0.56 0.17 0.11 0) *
##         3) reimbursement2008>=1565 7858 4988 B2 (0.36 0.37 0.17 0.089 0.012)  
##           6) reimbursement2008< 3425 3262 1635 B1 (0.5 0.32 0.13 0.048 0.0049)  
##            12) ihd< 0.5 1087  442 B1 (0.59 0.26 0.11 0.033 0.0037)  
##              24) kidney< 0.5 941  358 B1 (0.62 0.24 0.1 0.031 0.0043)  
##                48) heart.failure< 0.5 680  234 B1 (0.66 0.23 0.087 0.029 0.0029)  
##                  96) reimbursement2008< 2605 524  172 B1 (0.67 0.2 0.099 0.031 0.0019)  
##                   192) age< 96.5 517  167 B1 (0.68 0.19 0.097 0.031 0.0019)  
##                     384) depression< 0.5 395  119 B1 (0.7 0.18 0.099 0.023 0.0025)  
##                       768) age>=68.5 288   79 B1 (0.73 0.15 0.097 0.028 0)  
##                        1536) arthritis>=0.5 47   11 B1 (0.77 0.064 0.17 0 0)  
##                          3072) reimbursement2008>=1655 40    7 B1 (0.82 0.075 0.1 0 0) *
##                          3073) reimbursement2008< 1655 7    3 B3 (0.43 0 0.57 0 0) *
##                        1537) arthritis< 0.5 241   68 B1 (0.72 0.17 0.083 0.033 0) *
##                       769) age< 68.5 107   40 B1 (0.63 0.25 0.1 0.0093 0.0093)  
##                        1538) arthritis< 0.5 92   31 B1 (0.66 0.24 0.076 0.011 0.011)  
##                          3076) osteoporosis>=0.5 23    5 B1 (0.78 0.13 0.043 0.043 0) *
##                          3077) osteoporosis< 0.5 69   26 B1 (0.62 0.28 0.087 0 0.014)  
##                            6154) reimbursement2008< 2295 59   20 B1 (0.66 0.25 0.068 0 0.017)  
##                             12308) reimbursement2008>=2050 15    2 B1 (0.87 0.13 0 0 0) *
##                             12309) reimbursement2008< 2050 44   18 B1 (0.59 0.3 0.091 0 0.023)  
##                               24618) diabetes>=0.5 16    4 B1 (0.75 0.12 0.12 0 0) *
##                               24619) diabetes< 0.5 28   14 B1 (0.5 0.39 0.071 0 0.036)  
##                                 49238) reimbursement2008< 1880 20    7 B1 (0.65 0.35 0 0 0) *
##                                 49239) reimbursement2008>=1880 8    4 B2 (0.12 0.5 0.25 0 0.12) *
##                            6155) reimbursement2008>=2295 10    6 B1 (0.4 0.4 0.2 0 0) *
##                        1539) arthritis>=0.5 15    9 B1 (0.4 0.33 0.27 0 0) *
##                     385) depression>=0.5 122   48 B1 (0.61 0.25 0.09 0.057 0)  
##                       770) age< 64 22    2 B1 (0.91 0.091 0 0 0) *
##                       771) age>=64 100   46 B1 (0.54 0.28 0.11 0.07 0)  
##                        1542) age< 79.5 72   29 B1 (0.6 0.29 0.083 0.028 0)  
##                          3084) arthritis< 0.5 58   24 B1 (0.59 0.34 0.069 0 0)  
##                            6168) reimbursement2008< 2415 49   19 B1 (0.61 0.31 0.082 0 0)  
##                             12336) reimbursement2008>=2155 11    2 B1 (0.82 0.18 0 0 0) *
##                             12337) reimbursement2008< 2155 38   17 B1 (0.55 0.34 0.11 0 0)  
##                               24674) reimbursement2008< 2020 29   11 B1 (0.62 0.31 0.069 0 0) *
##                               24675) reimbursement2008>=2020 9    5 B2 (0.33 0.44 0.22 0 0) *
##                            6169) reimbursement2008>=2415 9    4 B2 (0.44 0.56 0 0 0) *
##                          3085) arthritis>=0.5 14    5 B1 (0.64 0.071 0.14 0.14 0) *
##                        1543) age>=79.5 28   17 B1 (0.39 0.25 0.18 0.18 0)  
##                          3086) arthritis>=0.5 7    2 B1 (0.71 0.14 0 0.14 0) *
##                          3087) arthritis< 0.5 21   15 B1 (0.29 0.29 0.24 0.19 0)  
##                            6174) reimbursement2008< 2170 13    8 B2 (0.31 0.38 0.23 0.077 0) *
##                            6175) reimbursement2008>=2170 8    5 B4 (0.25 0.12 0.25 0.38 0) *
##                   193) age>=96.5 7    4 B2 (0.29 0.43 0.29 0 0) *
##                  97) reimbursement2008>=2605 156   62 B1 (0.6 0.32 0.045 0.026 0.0064)  
##                   194) arthritis< 0.5 118   40 B1 (0.66 0.26 0.051 0.017 0.0085)  
##                     388) age< 69.5 45   11 B1 (0.76 0.18 0.044 0.022 0) *
##                     389) age>=69.5 73   29 B1 (0.6 0.32 0.055 0.014 0.014)  
##                       778) reimbursement2008< 3390 66   27 B1 (0.59 0.35 0.045 0 0.015)  
##                        1556) age< 80.5 41   17 B1 (0.59 0.41 0 0 0)  
##                          3112) reimbursement2008>=2765 30   10 B1 (0.67 0.33 0 0 0)  
##                            6224) age< 77.5 23    5 B1 (0.78 0.22 0 0 0) *
##                            6225) age>=77.5 7    2 B2 (0.29 0.71 0 0 0) *
##                          3113) reimbursement2008< 2765 11    4 B2 (0.36 0.64 0 0 0) *
##                        1557) age>=80.5 25   10 B1 (0.6 0.24 0.12 0 0.04)  
##                          3114) reimbursement2008< 3090 18    5 B1 (0.72 0.11 0.17 0 0) *
##                          3115) reimbursement2008>=3090 7    3 B2 (0.29 0.57 0 0 0.14) *
##                       779) reimbursement2008>=3390 7    2 B1 (0.71 0 0.14 0.14 0) *
##                   195) arthritis>=0.5 38   19 B2 (0.42 0.5 0.026 0.053 0)  
##                     390) diabetes< 0.5 12    4 B1 (0.67 0.25 0 0.083 0) *
##                     391) diabetes>=0.5 26   10 B2 (0.31 0.62 0.038 0.038 0)  
##                       782) depression>=0.5 7    3 B1 (0.57 0.43 0 0 0) *
##                       783) depression< 0.5 19    6 B2 (0.21 0.68 0.053 0.053 0) *
##                49) heart.failure>=0.5 261  124 B1 (0.52 0.29 0.14 0.034 0.0077)  
##                  98) diabetes< 0.5 110   42 B1 (0.62 0.24 0.082 0.055 0.0091)  
##                   196) depression>=0.5 32    8 B1 (0.75 0.12 0.12 0 0) *
##                   197) depression< 0.5 78   34 B1 (0.56 0.28 0.064 0.077 0.013)  
##                     394) reimbursement2008>=2685 20    5 B1 (0.75 0.15 0 0.1 0) *
##                     395) reimbursement2008< 2685 58   29 B1 (0.5 0.33 0.086 0.069 0.017)  
##                       790) reimbursement2008< 2425 50   23 B1 (0.54 0.32 0.04 0.08 0.02)  
##                        1580) age>=71.5 26    9 B1 (0.65 0.27 0.038 0 0.038) *
##                        1581) age< 71.5 24   14 B1 (0.42 0.38 0.042 0.17 0)  
##                          3162) age< 68.5 17    8 B1 (0.53 0.29 0.059 0.12 0) *
##                          3163) age>=68.5 7    3 B2 (0.14 0.57 0 0.29 0) *
##                       791) reimbursement2008>=2425 8    5 B2 (0.25 0.38 0.38 0 0) *
##                  99) diabetes>=0.5 151   82 B1 (0.46 0.33 0.19 0.02 0.0066)  
##                   198) reimbursement2008>=1675 140   74 B1 (0.47 0.31 0.19 0.021 0.0071)  
##                     396) reimbursement2008< 1775 10    3 B1 (0.7 0 0.3 0 0) *
##                     397) reimbursement2008>=1775 130   71 B1 (0.45 0.33 0.18 0.023 0.0077)  
##                       794) reimbursement2008>=3265 9    2 B1 (0.78 0.11 0.11 0 0) *
##                       795) reimbursement2008< 3265 121   69 B1 (0.43 0.35 0.19 0.025 0.0083)  
##                        1590) reimbursement2008< 3190 113   62 B1 (0.45 0.33 0.19 0.027 0.0088)  
##                          3180) reimbursement2008>=3055 8    1 B1 (0.88 0 0 0.12 0) *
##                          3181) reimbursement2008< 3055 105   61 B1 (0.42 0.35 0.2 0.019 0.0095)  
##                            6362) age>=75.5 45   22 B1 (0.51 0.29 0.18 0 0.022)  
##                             12724) arthritis< 0.5 32   13 B1 (0.59 0.19 0.19 0 0.031) *
##                             12725) arthritis>=0.5 13    6 B2 (0.31 0.54 0.15 0 0) *
##                            6363) age< 75.5 60   36 B2 (0.35 0.4 0.22 0.033 0)  
##                             12726) reimbursement2008>=2215 36   20 B1 (0.44 0.28 0.22 0.056 0)  
##                               25452) reimbursement2008< 2400 12    5 B1 (0.58 0.083 0.33 0 0) *
##                               25453) reimbursement2008>=2400 24   15 B1 (0.38 0.38 0.17 0.083 0)  
##                                 50906) age< 70 16    9 B2 (0.38 0.44 0.19 0 0) *
##                                 50907) age>=70 8    5 B1 (0.38 0.25 0.12 0.25 0) *
##                             12727) reimbursement2008< 2215 24   10 B2 (0.21 0.58 0.21 0 0) *
##                        1591) reimbursement2008>=3190 8    3 B2 (0.12 0.62 0.25 0 0) *
##                   199) reimbursement2008< 1675 11    4 B2 (0.27 0.64 0.091 0 0) *
##              25) kidney>=0.5 146   84 B1 (0.42 0.34 0.18 0.048 0)  
##                50) age< 74.5 82   38 B1 (0.54 0.27 0.15 0.049 0)  
##                 100) age>=63.5 63   25 B1 (0.6 0.19 0.14 0.063 0) *
##                 101) age< 63.5 19    9 B2 (0.32 0.53 0.16 0 0) *
##                51) age>=74.5 64   36 B2 (0.28 0.44 0.23 0.047 0)  
##                 102) age>=84.5 28   12 B2 (0.32 0.57 0.071 0.036 0) *
##                 103) age< 84.5 36   23 B3 (0.25 0.33 0.36 0.056 0)  
##                   206) reimbursement2008< 1990 10    4 B1 (0.6 0.2 0.2 0 0) *
##                   207) reimbursement2008>=1990 26   15 B3 (0.12 0.38 0.42 0.077 0)  
##                     414) age< 78.5 12    5 B2 (0.17 0.58 0.17 0.083 0) *
##                     415) age>=78.5 14    5 B3 (0.071 0.21 0.64 0.071 0) *
##            13) ihd>=0.5 2175 1193 B1 (0.45 0.35 0.13 0.055 0.0055)  
##              26) reimbursement2008< 2515 1275  637 B1 (0.5 0.32 0.12 0.053 0.0063)  
##                52) depression< 0.5 880  412 B1 (0.53 0.29 0.12 0.052 0.008)  
##                 104) stroke< 0.5 849  390 B1 (0.54 0.29 0.11 0.053 0.0082)  
##                   208) age>=73.5 406  162 B1 (0.6 0.26 0.086 0.047 0.0074)  
##                     416) arthritis< 0.5 307  115 B1 (0.63 0.23 0.091 0.046 0.0065)  
##                       832) diabetes>=0.5 163   55 B1 (0.66 0.17 0.11 0.049 0.0061) *
##                       833) diabetes< 0.5 144   60 B1 (0.58 0.3 0.069 0.042 0.0069)  
##                        1666) heart.failure< 0.5 86   31 B1 (0.64 0.22 0.081 0.047 0.012)  
##                          3332) alzheimers< 0.5 70   21 B1 (0.7 0.17 0.071 0.043 0.014) *
##                          3333) alzheimers>=0.5 16    9 B2 (0.38 0.44 0.12 0.062 0) *
##                        1667) heart.failure>=0.5 58   29 B1 (0.5 0.41 0.052 0.034 0)  
##                          3334) age< 75.5 8    2 B1 (0.75 0.12 0.12 0 0) *
##                          3335) age>=75.5 50   27 B1 (0.46 0.46 0.04 0.04 0)  
##                            6670) age< 89.5 42   21 B1 (0.5 0.43 0.048 0.024 0)  
##                             13340) reimbursement2008< 2305 34   15 B1 (0.56 0.41 0.029 0 0)  
##                               26680) reimbursement2008>=2070 7    2 B1 (0.71 0.14 0.14 0 0) *
##                               26681) reimbursement2008< 2070 27   13 B1 (0.52 0.48 0 0 0)  
##                                 53362) age>=79.5 20    8 B1 (0.6 0.4 0 0 0)  
##                                  106724) reimbursement2008< 1790 9    2 B1 (0.78 0.22 0 0 0) *
##                                  106725) reimbursement2008>=1790 11    5 B2 (0.45 0.55 0 0 0) *
##                                 53363) age< 79.5 7    2 B2 (0.29 0.71 0 0 0) *
##                             13341) reimbursement2008>=2305 8    4 B2 (0.25 0.5 0.12 0.12 0) *
##                            6671) age>=89.5 8    3 B2 (0.25 0.62 0 0.12 0) *
##                     417) arthritis>=0.5 99   47 B1 (0.53 0.34 0.071 0.051 0.01)  
##                       834) copd>=0.5 11    2 B1 (0.82 0.091 0.091 0 0) *
##                       835) copd< 0.5 88   45 B1 (0.49 0.38 0.068 0.057 0.011)  
##                        1670) alzheimers< 0.5 63   32 B1 (0.49 0.43 0.063 0 0.016)  
##                          3340) reimbursement2008< 2015 33   14 B1 (0.58 0.3 0.091 0 0.03)  
##                            6680) age>=77.5 19    5 B1 (0.74 0.16 0.11 0 0) *
##                            6681) age< 77.5 14    7 B2 (0.36 0.5 0.071 0 0.071) *
##                          3341) reimbursement2008>=2015 30   13 B2 (0.4 0.57 0.033 0 0)  
##                            6682) osteoporosis>=0.5 12    5 B1 (0.58 0.42 0 0 0) *
##                            6683) osteoporosis< 0.5 18    6 B2 (0.28 0.67 0.056 0 0) *
##                        1671) alzheimers>=0.5 25   13 B1 (0.48 0.24 0.08 0.2 0)  
##                          3342) diabetes< 0.5 10    2 B1 (0.8 0 0.1 0.1 0) *
##                          3343) diabetes>=0.5 15    9 B2 (0.27 0.4 0.067 0.27 0) *
##                   209) age< 73.5 443  228 B1 (0.49 0.32 0.13 0.059 0.009)  
##                     418) heart.failure< 0.5 261  117 B1 (0.55 0.28 0.11 0.057 0.0038)  
##                       836) kidney< 0.5 228   93 B1 (0.59 0.27 0.088 0.048 0.0044)  
##                        1672) age>=43.5 218   85 B1 (0.61 0.26 0.083 0.046 0.0046)  
##                          3344) reimbursement2008< 2485 211   80 B1 (0.62 0.24 0.085 0.047 0.0047)  
##                            6688) diabetes< 0.5 96   29 B1 (0.7 0.2 0.073 0.031 0) *
##                            6689) diabetes>=0.5 115   51 B1 (0.56 0.28 0.096 0.061 0.0087)  
##                             13378) age< 60 20    5 B1 (0.75 0.25 0 0 0) *
##                             13379) age>=60 95   46 B1 (0.52 0.28 0.12 0.074 0.011)  
##                               26758) reimbursement2008< 1735 27    8 B1 (0.7 0.15 0.11 0 0.037) *
##                               26759) reimbursement2008>=1735 68   38 B1 (0.44 0.34 0.12 0.1 0)  
##                                 53518) reimbursement2008>=2145 29   13 B1 (0.55 0.24 0.17 0.034 0)  
##                                  107036) age>=69.5 17    5 B1 (0.71 0.12 0.18 0 0) *
##                                  107037) age< 69.5 12    7 B2 (0.33 0.42 0.17 0.083 0) *
##                                 53519) reimbursement2008< 2145 39   23 B2 (0.36 0.41 0.077 0.15 0)  
##                                  107038) reimbursement2008< 2065 30   17 B1 (0.43 0.37 0.067 0.13 0)  
##                                    214076) reimbursement2008>=1910 12    4 B1 (0.67 0.17 0 0.17 0) *
##                                    214077) reimbursement2008< 1910 18    9 B2 (0.28 0.5 0.11 0.11 0) *
##                                  107039) reimbursement2008>=2065 9    4 B2 (0.11 0.56 0.11 0.22 0) *
##                          3345) reimbursement2008>=2485 7    2 B2 (0.29 0.71 0 0 0) *
##                        1673) age< 43.5 10    5 B2 (0.2 0.5 0.2 0.1 0) *
##                       837) kidney>=0.5 33   21 B2 (0.27 0.36 0.24 0.12 0)  
##                        1674) age< 72.5 26   16 B2 (0.35 0.38 0.12 0.15 0)  
##                          3348) age>=54.5 18   10 B1 (0.44 0.28 0.11 0.17 0) *
##                          3349) age< 54.5 8    3 B2 (0.12 0.62 0.12 0.12 0) *
##                        1675) age>=72.5 7    2 B3 (0 0.29 0.71 0 0) *
##                     419) heart.failure>=0.5 182  111 B1 (0.39 0.37 0.16 0.06 0.016)  
##                       838) copd< 0.5 146   85 B2 (0.38 0.42 0.13 0.055 0.014)  
##                        1676) reimbursement2008< 2235 115   67 B1 (0.42 0.4 0.096 0.07 0.017)  
##                          3352) age>=55.5 98   56 B2 (0.42 0.43 0.061 0.082 0.01)  
##                            6704) reimbursement2008< 2165 88   48 B2 (0.41 0.45 0.068 0.057 0.011)  
##                             13408) reimbursement2008< 1925 55   29 B1 (0.47 0.44 0.036 0.055 0)  
##                               26816) reimbursement2008< 1865 45   23 B2 (0.44 0.49 0.044 0.022 0)  
##                                 53632) age>=66.5 33   16 B1 (0.52 0.42 0.03 0.03 0)  
##                                  107264) reimbursement2008< 1715 18    7 B1 (0.61 0.33 0 0.056 0) *
##                                  107265) reimbursement2008>=1715 15    7 B2 (0.4 0.53 0.067 0 0) *
##                                 53633) age< 66.5 12    4 B2 (0.25 0.67 0.083 0 0) *
##                               26817) reimbursement2008>=1865 10    4 B1 (0.6 0.2 0 0.2 0) *
##                             13409) reimbursement2008>=1925 33   17 B2 (0.3 0.48 0.12 0.061 0.03)  
##                               26818) age>=72.5 7    1 B2 (0.14 0.86 0 0 0) *
##                               26819) age< 72.5 26   16 B2 (0.35 0.38 0.15 0.077 0.038)  
##                                 53638) reimbursement2008>=2005 14    7 B1 (0.5 0.36 0.071 0.071 0) *
##                                 53639) reimbursement2008< 2005 12    7 B2 (0.17 0.42 0.25 0.083 0.083) *
##                            6705) reimbursement2008>=2165 10    5 B1 (0.5 0.2 0 0.3 0) *
##                          3353) age< 55.5 17   10 B1 (0.41 0.24 0.29 0 0.059) *
##                        1677) reimbursement2008>=2235 31   16 B2 (0.26 0.48 0.26 0 0)  
##                          3354) age>=62 23   14 B2 (0.35 0.39 0.26 0 0)  
##                            6708) reimbursement2008>=2305 16    8 B2 (0.31 0.5 0.19 0 0) *
##                            6709) reimbursement2008< 2305 7    4 B1 (0.43 0.14 0.43 0 0) *
##                          3355) age< 62 8    2 B2 (0 0.75 0.25 0 0) *
##                       839) copd>=0.5 36   21 B1 (0.42 0.19 0.28 0.083 0.028)  
##                        1678) age>=69.5 11    5 B1 (0.55 0.36 0.091 0 0) *
##                        1679) age< 69.5 25   16 B1 (0.36 0.12 0.36 0.12 0.04)  
##                          3358) diabetes< 0.5 8    4 B1 (0.5 0.12 0.12 0.25 0) *
##                          3359) diabetes>=0.5 17    9 B3 (0.29 0.12 0.47 0.059 0.059) *
##                 105) stroke>=0.5 31   20 B2 (0.29 0.35 0.32 0.032 0)  
##                   210) age>=75.5 17    8 B2 (0.24 0.53 0.24 0 0) *
##                   211) age< 75.5 14    8 B3 (0.36 0.14 0.43 0.071 0) *
##                53) depression>=0.5 395  225 B1 (0.43 0.38 0.13 0.056 0.0025)  
##                 106) age>=84.5 80   34 B1 (0.57 0.29 0.062 0.075 0)  
##                   212) age< 93.5 55   18 B1 (0.67 0.22 0.055 0.055 0) *
##                   213) age>=93.5 25   14 B2 (0.36 0.44 0.08 0.12 0)  
##                     426) age>=97.5 15    8 B1 (0.47 0.27 0.13 0.13 0) *
##                     427) age< 97.5 10    3 B2 (0.2 0.7 0 0.1 0) *
##                 107) age< 84.5 315  186 B2 (0.39 0.41 0.14 0.051 0.0032)  
##                   214) cancer< 0.5 298  176 B1 (0.41 0.39 0.14 0.05 0.0034)  
##                     428) age< 71.5 162   86 B1 (0.47 0.33 0.12 0.074 0.0062)  
##                       856) reimbursement2008< 1975 76   28 B1 (0.63 0.24 0.053 0.066 0.013)  
##                        1712) copd< 0.5 62   20 B1 (0.68 0.18 0.065 0.065 0.016)  
##                          3424) heart.failure>=0.5 28    6 B1 (0.79 0.036 0.071 0.071 0.036) *
##                          3425) heart.failure< 0.5 34   14 B1 (0.59 0.29 0.059 0.059 0)  
##                            6850) reimbursement2008>=1865 10    2 B1 (0.8 0 0.1 0.1 0) *
##                            6851) reimbursement2008< 1865 24   12 B1 (0.5 0.42 0.042 0.042 0)  
##                             13702) reimbursement2008< 1775 14    4 B1 (0.71 0.29 0 0 0) *
##                             13703) reimbursement2008>=1775 10    4 B2 (0.2 0.6 0.1 0.1 0) *
##                        1713) copd>=0.5 14    7 B2 (0.43 0.5 0 0.071 0) *
##                       857) reimbursement2008>=1975 86   51 B2 (0.33 0.41 0.19 0.081 0)  
##                        1714) alzheimers< 0.5 54   33 B1 (0.39 0.31 0.22 0.074 0)  
##                          3428) reimbursement2008>=2305 25   11 B1 (0.56 0.28 0.12 0.04 0) *
##                          3429) reimbursement2008< 2305 29   19 B2 (0.24 0.34 0.31 0.1 0)  
##                            6858) age>=55 22   12 B2 (0.18 0.45 0.27 0.091 0) *
##                            6859) age< 55 7    4 B1 (0.43 0 0.43 0.14 0) *
##                        1715) alzheimers>=0.5 32   14 B2 (0.22 0.56 0.12 0.094 0) *
##                     429) age>=71.5 136   72 B2 (0.34 0.47 0.17 0.022 0)  
##                       858) reimbursement2008>=1705 117   57 B2 (0.33 0.51 0.15 0.0085 0)  
##                        1716) reimbursement2008>=2445 8    3 B1 (0.62 0.25 0.12 0 0) *
##                        1717) reimbursement2008< 2445 109   51 B2 (0.31 0.53 0.15 0.0092 0)  
##                          3434) reimbursement2008>=2375 10    2 B2 (0.2 0.8 0 0 0) *
##                          3435) reimbursement2008< 2375 99   49 B2 (0.32 0.51 0.16 0.01 0)  
##                            6870) reimbursement2008>=2045 46   27 B1 (0.41 0.41 0.17 0 0)  
##                             13740) copd>=0.5 7    2 B1 (0.71 0 0.29 0 0) *
##                             13741) copd< 0.5 39   20 B2 (0.36 0.49 0.15 0 0)  
##                               27482) heart.failure>=0.5 15    6 B1 (0.6 0.33 0.067 0 0) *
##                               27483) heart.failure< 0.5 24   10 B2 (0.21 0.58 0.21 0 0) *
##                            6871) reimbursement2008< 2045 53   22 B2 (0.25 0.58 0.15 0.019 0)  
##                             13742) reimbursement2008< 1795 13    6 B1 (0.54 0.46 0 0 0) *
##                             13743) reimbursement2008>=1795 40   15 B2 (0.15 0.62 0.2 0.025 0)  
##                               27486) age< 78.5 33   10 B2 (0.12 0.7 0.15 0.03 0) *
##                               27487) age>=78.5 7    4 B3 (0.29 0.29 0.43 0 0) *
##                       859) reimbursement2008< 1705 19   12 B1 (0.37 0.21 0.32 0.11 0) *
##                   215) cancer>=0.5 17    5 B2 (0.12 0.71 0.12 0.059 0) *
##              27) reimbursement2008>=2515 900  539 B2 (0.38 0.4 0.16 0.057 0.0044)  
##                54) arthritis< 0.5 614  349 B1 (0.43 0.35 0.15 0.06 0.0033)  
##                 108) heart.failure< 0.5 317  155 B1 (0.51 0.32 0.13 0.038 0.0063)  
##                   216) cancer< 0.5 281  127 B1 (0.55 0.28 0.12 0.043 0.0071)  
##                     432) age< 67.5 68   24 B1 (0.65 0.26 0.044 0.044 0)  
##                       864) age>=64.5 21    3 B1 (0.86 0.095 0 0.048 0) *
##                       865) age< 64.5 47   21 B1 (0.55 0.34 0.064 0.043 0)  
##                        1730) reimbursement2008>=2765 37   15 B1 (0.59 0.27 0.081 0.054 0) *
##                        1731) reimbursement2008< 2765 10    4 B2 (0.4 0.6 0 0 0) *
##                     433) age>=67.5 213  103 B1 (0.52 0.28 0.15 0.042 0.0094)  
##                       866) diabetes< 0.5 92   35 B1 (0.62 0.23 0.11 0.043 0)  
##                        1732) reimbursement2008>=3170 23    4 B1 (0.83 0.087 0.087 0 0) *
##                        1733) reimbursement2008< 3170 69   31 B1 (0.55 0.28 0.12 0.058 0)  
##                          3466) alzheimers>=0.5 14    3 B1 (0.79 0.14 0 0.071 0) *
##                          3467) alzheimers< 0.5 55   28 B1 (0.49 0.31 0.15 0.055 0)  
##                            6934) age< 83.5 41   23 B1 (0.44 0.41 0.15 0 0)  
##                             13868) reimbursement2008>=2680 30   14 B1 (0.53 0.37 0.1 0 0)  
##                               27736) depression< 0.5 22    8 B1 (0.64 0.32 0.045 0 0) *
##                               27737) depression>=0.5 8    4 B2 (0.25 0.5 0.25 0 0) *
##                             13869) reimbursement2008< 2680 11    5 B2 (0.18 0.55 0.27 0 0) *
##                            6935) age>=83.5 14    5 B1 (0.64 0 0.14 0.21 0) *
##                       867) diabetes>=0.5 121   68 B1 (0.44 0.32 0.18 0.041 0.017)  
##                        1734) age>=69.5 104   54 B1 (0.48 0.28 0.18 0.038 0.019)  
##                          3468) age< 79.5 58   25 B1 (0.57 0.19 0.17 0.034 0.034)  
##                            6936) reimbursement2008>=3325 7    0 B1 (1 0 0 0 0) *
##                            6937) reimbursement2008< 3325 51   25 B1 (0.51 0.22 0.2 0.039 0.039)  
##                             13874) reimbursement2008< 2865 24    9 B1 (0.62 0.12 0.21 0 0.042) *
##                             13875) reimbursement2008>=2865 27   16 B1 (0.41 0.3 0.19 0.074 0.037)  
##                               27750) reimbursement2008>=3040 20   10 B1 (0.5 0.3 0.1 0.1 0)  
##                                 55500) alzheimers>=0.5 8    2 B1 (0.75 0.12 0 0.12 0) *
##                                 55501) alzheimers< 0.5 12    7 B2 (0.33 0.42 0.17 0.083 0) *
##                               27751) reimbursement2008< 3040 7    4 B3 (0.14 0.29 0.43 0 0.14) *
##                          3469) age>=79.5 46   28 B2 (0.37 0.39 0.2 0.043 0)  
##                            6938) kidney< 0.5 33   18 B2 (0.39 0.45 0.12 0.03 0)  
##                             13876) osteoporosis>=0.5 7    2 B2 (0.29 0.71 0 0 0) *
##                             13877) osteoporosis< 0.5 26   15 B1 (0.42 0.38 0.15 0.038 0)  
##                               27754) reimbursement2008< 2785 12    5 B2 (0.33 0.58 0.083 0 0) *
##                               27755) reimbursement2008>=2785 14    7 B1 (0.5 0.21 0.21 0.071 0) *
##                            6939) kidney>=0.5 13    8 B3 (0.31 0.23 0.38 0.077 0) *
##                        1735) age< 69.5 17    7 B2 (0.18 0.59 0.18 0.059 0) *
##                   217) cancer>=0.5 36   14 B2 (0.22 0.61 0.17 0 0)  
##                     434) reimbursement2008< 2770 10    5 B1 (0.5 0.3 0.2 0 0) *
##                     435) reimbursement2008>=2770 26    7 B2 (0.12 0.73 0.15 0 0) *
##                 109) heart.failure>=0.5 297  181 B2 (0.35 0.39 0.18 0.084 0)  
##                   218) kidney< 0.5 213  130 B1 (0.39 0.35 0.15 0.1 0)  
##                     436) alzheimers< 0.5 146   81 B1 (0.45 0.36 0.11 0.089 0)  
##                       872) reimbursement2008>=2585 133   70 B1 (0.47 0.36 0.083 0.083 0)  
##                        1744) reimbursement2008>=3365 8    1 B1 (0.88 0.12 0 0 0) *
##                        1745) reimbursement2008< 3365 125   69 B1 (0.45 0.38 0.088 0.088 0)  
##                          3490) reimbursement2008< 2925 67   31 B1 (0.54 0.27 0.09 0.1 0)  
##                            6980) diabetes< 0.5 23    8 B1 (0.65 0.087 0.13 0.13 0) *
##                            6981) diabetes>=0.5 44   23 B1 (0.48 0.36 0.068 0.091 0)  
##                             13962) reimbursement2008< 2715 23   12 B2 (0.43 0.48 0.043 0.043 0)  
##                               27924) reimbursement2008< 2630 9    3 B1 (0.67 0.22 0 0.11 0) *
##                               27925) reimbursement2008>=2630 14    5 B2 (0.29 0.64 0.071 0 0) *
##                             13963) reimbursement2008>=2715 21   10 B1 (0.52 0.24 0.095 0.14 0)  
##                               27926) age>=71.5 12    4 B1 (0.67 0.083 0.083 0.17 0) *
##                               27927) age< 71.5 9    5 B2 (0.33 0.44 0.11 0.11 0) *
##                          3491) reimbursement2008>=2925 58   29 B2 (0.34 0.5 0.086 0.069 0)  
##                            6982) age< 67.5 13    5 B1 (0.62 0.31 0.077 0 0) *
##                            6983) age>=67.5 45   20 B2 (0.27 0.56 0.089 0.089 0)  
##                             13966) reimbursement2008>=3285 10    5 B1 (0.5 0.3 0.1 0.1 0) *
##                             13967) reimbursement2008< 3285 35   13 B2 (0.2 0.63 0.086 0.086 0) *
##                       873) reimbursement2008< 2585 13    8 B3 (0.15 0.31 0.38 0.15 0) *
##                     437) alzheimers>=0.5 67   44 B2 (0.27 0.34 0.25 0.13 0)  
##                       874) reimbursement2008< 2605 11    6 B1 (0.45 0.18 0.27 0.091 0) *
##                       875) reimbursement2008>=2605 56   35 B2 (0.23 0.38 0.25 0.14 0)  
##                        1750) reimbursement2008< 2755 10    3 B2 (0.1 0.7 0.1 0.1 0) *
##                        1751) reimbursement2008>=2755 46   32 B2 (0.26 0.3 0.28 0.15 0)  
##                          3502) reimbursement2008>=2845 39   27 B1 (0.31 0.31 0.23 0.15 0)  
##                            7004) reimbursement2008>=3120 19   10 B2 (0.21 0.47 0.21 0.11 0) *
##                            7005) reimbursement2008< 3120 20   12 B1 (0.4 0.15 0.25 0.2 0)  
##                             14010) reimbursement2008< 2955 8    3 B1 (0.62 0.25 0.12 0 0) *
##                             14011) reimbursement2008>=2955 12    8 B3 (0.25 0.083 0.33 0.33 0) *
##                          3503) reimbursement2008< 2845 7    3 B3 (0 0.29 0.57 0.14 0) *
##                   219) kidney>=0.5 84   43 B2 (0.24 0.49 0.24 0.036 0)  
##                     438) copd< 0.5 57   28 B2 (0.28 0.51 0.16 0.053 0)  
##                       876) reimbursement2008>=2735 41   16 B2 (0.22 0.61 0.15 0.024 0) *
##                       877) reimbursement2008< 2735 16    9 B1 (0.44 0.25 0.19 0.12 0) *
##                     439) copd>=0.5 27   15 B2 (0.15 0.44 0.41 0 0)  
##                       878) age>=84.5 9    5 B1 (0.44 0.22 0.33 0 0) *
##                       879) age< 84.5 18    8 B2 (0 0.56 0.44 0 0) *
##                55) arthritis>=0.5 286  141 B2 (0.28 0.51 0.16 0.049 0.007)  
##                 110) reimbursement2008< 3015 174   97 B2 (0.31 0.44 0.21 0.034 0.0057)  
##                   220) reimbursement2008< 2965 157   84 B2 (0.32 0.46 0.18 0.032 0.0064)  
##                     440) stroke< 0.5 150   83 B2 (0.33 0.45 0.18 0.033 0.0067)  
##                       880) age< 89.5 142   81 B2 (0.35 0.43 0.19 0.028 0.007)  
##                        1760) kidney< 0.5 104   57 B2 (0.37 0.45 0.13 0.038 0.0096)  
##                          3520) reimbursement2008>=2785 40   22 B1 (0.45 0.38 0.12 0.025 0.025)  
##                            7040) age< 80.5 32   15 B1 (0.53 0.34 0.12 0 0)  
##                             14080) depression< 0.5 18    6 B1 (0.67 0.22 0.11 0 0) *
##                             14081) depression>=0.5 14    7 B2 (0.36 0.5 0.14 0 0) *
##                            7041) age>=80.5 8    4 B2 (0.12 0.5 0.12 0.12 0.12) *
##                          3521) reimbursement2008< 2785 64   32 B2 (0.31 0.5 0.14 0.047 0)  
##                            7042) reimbursement2008>=2565 52   23 B2 (0.29 0.56 0.13 0.019 0) *
##                            7043) reimbursement2008< 2565 12    7 B1 (0.42 0.25 0.17 0.17 0) *
##                        1761) kidney>=0.5 38   24 B2 (0.29 0.37 0.34 0 0)  
##                          3522) alzheimers>=0.5 12    5 B2 (0.33 0.58 0.083 0 0) *
##                          3523) alzheimers< 0.5 26   14 B3 (0.27 0.27 0.46 0 0)  
##                            7046) diabetes>=0.5 19   12 B2 (0.32 0.37 0.32 0 0) *
##                            7047) diabetes< 0.5 7    1 B3 (0.14 0 0.86 0 0) *
##                       881) age>=89.5 8    2 B2 (0.12 0.75 0 0.12 0) *
##                     441) stroke>=0.5 7    1 B2 (0 0.86 0.14 0 0) *
##                   221) reimbursement2008>=2965 17    9 B3 (0.24 0.24 0.47 0.059 0) *
##                 111) reimbursement2008>=3015 112   44 B2 (0.22 0.61 0.089 0.071 0.0089)  
##                   222) kidney< 0.5 81   38 B2 (0.28 0.53 0.099 0.074 0.012)  
##                     444) reimbursement2008>=3075 70   35 B2 (0.31 0.5 0.11 0.057 0.014)  
##                       888) reimbursement2008< 3265 40   23 B1 (0.43 0.4 0.12 0.025 0.025)  
##                        1776) age>=82.5 11    4 B2 (0.27 0.64 0.091 0 0) *
##                        1777) age< 82.5 29   15 B1 (0.48 0.31 0.14 0.034 0.034)  
##                          3554) heart.failure< 0.5 11    2 B1 (0.82 0.18 0 0 0) *
##                          3555) heart.failure>=0.5 18   11 B2 (0.28 0.39 0.22 0.056 0.056) *
##                       889) reimbursement2008>=3265 30   11 B2 (0.17 0.63 0.1 0.1 0) *
##                     445) reimbursement2008< 3075 11    3 B2 (0.091 0.73 0 0.18 0) *
##                   223) kidney>=0.5 31    6 B2 (0.065 0.81 0.065 0.065 0) *
##           7) reimbursement2008>=3425 4596 2775 B2 (0.26 0.4 0.2 0.12 0.017)  
##            14) diabetes< 0.5 1002  558 B1 (0.44 0.33 0.17 0.054 0.003)  
##              28) depression< 0.5 682  335 B1 (0.51 0.3 0.14 0.048 0.0044)  
##                56) cancer< 0.5 563  252 B1 (0.55 0.28 0.13 0.036 0.0053)  
##                 112) arthritis< 0.5 419  169 B1 (0.6 0.26 0.1 0.031 0.0072)  
##                   224) osteoporosis< 0.5 330  125 B1 (0.62 0.23 0.11 0.03 0.0061)  
##                     448) ihd< 0.5 120   33 B1 (0.72 0.17 0.067 0.033 0)  
##                       896) reimbursement2008>=8195 26    2 B1 (0.92 0.038 0.038 0 0) *
##                       897) reimbursement2008< 8195 94   31 B1 (0.67 0.21 0.074 0.043 0)  
##                        1794) heart.failure< 0.5 64   17 B1 (0.73 0.16 0.062 0.047 0) *
##                        1795) heart.failure>=0.5 30   14 B1 (0.53 0.33 0.1 0.033 0)  
##                          3590) copd< 0.5 23    9 B1 (0.61 0.26 0.087 0.043 0) *
##                          3591) copd>=0.5 7    3 B2 (0.29 0.57 0.14 0 0) *
##                     449) ihd>=0.5 210   92 B1 (0.56 0.27 0.13 0.029 0.0095)  
##                       898) reimbursement2008>=7060 89   32 B1 (0.64 0.24 0.079 0.034 0.011)  
##                        1796) reimbursement2008< 9310 22    3 B1 (0.86 0.091 0.045 0 0) *
##                        1797) reimbursement2008>=9310 67   29 B1 (0.57 0.28 0.09 0.045 0.015)  
##                          3594) reimbursement2008>=10695 56   21 B1 (0.62 0.27 0.054 0.036 0.018) *
##                          3595) reimbursement2008< 10695 11    7 B2 (0.27 0.36 0.27 0.091 0) *
##                       899) reimbursement2008< 7060 121   60 B1 (0.5 0.29 0.17 0.025 0.0083)  
##                        1798) reimbursement2008< 6145 105   46 B1 (0.56 0.26 0.16 0.019 0)  
##                          3596) age>=88.5 8    1 B1 (0.88 0.12 0 0 0) *
##                          3597) age< 88.5 97   45 B1 (0.54 0.27 0.18 0.021 0)  
##                            7194) age< 81.5 79   33 B1 (0.58 0.22 0.19 0.013 0)  
##                             14388) reimbursement2008< 4235 32   14 B1 (0.56 0.34 0.062 0.031 0) *
##                             14389) reimbursement2008>=4235 47   19 B1 (0.6 0.13 0.28 0 0)  
##                               28778) age>=70.5 22    6 B1 (0.73 0.091 0.18 0 0) *
##                               28779) age< 70.5 25   13 B1 (0.48 0.16 0.36 0 0)  
##                                 57558) reimbursement2008< 5500 18    7 B1 (0.61 0.11 0.28 0 0) *
##                                 57559) reimbursement2008>=5500 7    3 B3 (0.14 0.29 0.57 0 0) *
##                            7195) age>=81.5 18    9 B2 (0.33 0.5 0.11 0.056 0) *
##                        1799) reimbursement2008>=6145 16    8 B2 (0.12 0.5 0.25 0.062 0.062) *
##                   225) osteoporosis>=0.5 89   44 B1 (0.51 0.38 0.067 0.034 0.011)  
##                     450) reimbursement2008>=12275 15    3 B1 (0.8 0.067 0.067 0.067 0) *
##                     451) reimbursement2008< 12275 74   41 B1 (0.45 0.45 0.068 0.027 0.014)  
##                       902) copd< 0.5 60   30 B1 (0.5 0.38 0.083 0.033 0)  
##                        1804) age< 74.5 26    9 B1 (0.65 0.27 0.077 0 0) *
##                        1805) age>=74.5 34   18 B2 (0.38 0.47 0.088 0.059 0)  
##                          3610) age< 83.5 22    9 B2 (0.32 0.59 0.045 0.045 0) *
##                          3611) age>=83.5 12    6 B1 (0.5 0.25 0.17 0.083 0) *
##                       903) copd>=0.5 14    4 B2 (0.21 0.71 0 0 0.071) *
##                 113) arthritis>=0.5 144   83 B1 (0.42 0.33 0.2 0.049 0)  
##                   226) age< 73.5 58   27 B1 (0.53 0.26 0.14 0.069 0)  
##                     452) reimbursement2008>=6600 27    8 B1 (0.7 0.15 0.037 0.11 0) *
##                     453) reimbursement2008< 6600 31   19 B1 (0.39 0.35 0.23 0.032 0)  
##                       906) heart.failure>=0.5 16    8 B2 (0.31 0.5 0.19 0 0) *
##                       907) heart.failure< 0.5 15    8 B1 (0.47 0.2 0.27 0.067 0) *
##                   227) age>=73.5 86   54 B2 (0.35 0.37 0.24 0.035 0)  
##                     454) ihd< 0.5 14    6 B1 (0.57 0.21 0.14 0.071 0) *
##                     455) ihd>=0.5 72   43 B2 (0.31 0.4 0.26 0.028 0)  
##                       910) reimbursement2008< 4780 18    7 B2 (0.22 0.61 0.17 0 0) *
##                       911) reimbursement2008>=4780 54   36 B1 (0.33 0.33 0.3 0.037 0)  
##                        1822) reimbursement2008>=13120 22   11 B2 (0.32 0.5 0.14 0.045 0)  
##                          3644) reimbursement2008< 14605 7    1 B2 (0.14 0.86 0 0 0) *
##                          3645) reimbursement2008>=14605 15    9 B1 (0.4 0.33 0.2 0.067 0) *
##                        1823) reimbursement2008< 13120 32   19 B3 (0.34 0.22 0.41 0.031 0)  
##                          3646) copd>=0.5 9    5 B1 (0.44 0.33 0.11 0.11 0) *
##                          3647) copd< 0.5 23   11 B3 (0.3 0.17 0.52 0 0) *
##                57) cancer>=0.5 119   75 B2 (0.3 0.37 0.22 0.11 0)  
##                 114) reimbursement2008< 6095 55   34 B1 (0.38 0.27 0.22 0.13 0)  
##                   228) heart.failure< 0.5 42   24 B1 (0.43 0.36 0.095 0.12 0)  
##                     456) reimbursement2008< 3950 10    3 B2 (0.2 0.7 0.1 0 0) *
##                     457) reimbursement2008>=3950 32   16 B1 (0.5 0.25 0.094 0.16 0)  
##                       914) age>=64.5 25   12 B1 (0.52 0.28 0 0.2 0)  
##                        1828) copd< 0.5 18    7 B1 (0.61 0.17 0 0.22 0) *
##                        1829) copd>=0.5 7    3 B2 (0.29 0.57 0 0.14 0) *
##                       915) age< 64.5 7    4 B1 (0.43 0.14 0.43 0 0) *
##                   229) heart.failure>=0.5 13    5 B3 (0.23 0 0.62 0.15 0) *
##                 115) reimbursement2008>=6095 64   35 B2 (0.23 0.45 0.22 0.094 0)  
##                   230) copd< 0.5 41   18 B2 (0.22 0.56 0.12 0.098 0) *
##                   231) copd>=0.5 23   14 B3 (0.26 0.26 0.39 0.087 0)  
##                     462) reimbursement2008>=9740 12    7 B1 (0.42 0.17 0.25 0.17 0) *
##                     463) reimbursement2008< 9740 11    5 B3 (0.091 0.36 0.55 0 0) *
##              29) depression>=0.5 320  190 B2 (0.3 0.41 0.23 0.066 0)  
##                58) copd< 0.5 213  129 B2 (0.35 0.39 0.2 0.056 0)  
##                 116) age< 55.5 20    9 B1 (0.55 0.15 0.3 0 0) *
##                 117) age>=55.5 193  112 B2 (0.33 0.42 0.19 0.062 0)  
##                   234) age< 82.5 136   70 B2 (0.29 0.49 0.17 0.051 0)  
##                     468) heart.failure< 0.5 72   38 B2 (0.39 0.47 0.097 0.042 0)  
##                       936) reimbursement2008>=7260 27   11 B1 (0.59 0.3 0.074 0.037 0)  
##                        1872) reimbursement2008>=14045 11    5 B2 (0.45 0.55 0 0 0) *
##                        1873) reimbursement2008< 14045 16    5 B1 (0.69 0.12 0.12 0.062 0) *
##                       937) reimbursement2008< 7260 45   19 B2 (0.27 0.58 0.11 0.044 0)  
##                        1874) reimbursement2008< 3740 7    3 B1 (0.57 0.29 0.14 0 0) *
##                        1875) reimbursement2008>=3740 38   14 B2 (0.21 0.63 0.11 0.053 0)  
##                          3750) reimbursement2008< 4175 13    2 B2 (0.15 0.85 0 0 0) *
##                          3751) reimbursement2008>=4175 25   12 B2 (0.24 0.52 0.16 0.08 0)  
##                            7502) reimbursement2008< 5090 10    6 B1 (0.4 0.3 0.2 0.1 0) *
##                            7503) reimbursement2008>=5090 15    5 B2 (0.13 0.67 0.13 0.067 0) *
##                     469) heart.failure>=0.5 64   32 B2 (0.19 0.5 0.25 0.062 0)  
##                       938) ihd< 0.5 12    2 B2 (0.083 0.83 0.083 0 0) *
##                       939) ihd>=0.5 52   30 B2 (0.21 0.42 0.29 0.077 0)  
##                        1878) osteoporosis>=0.5 13    4 B2 (0.15 0.69 0.077 0.077 0) *
##                        1879) osteoporosis< 0.5 39   25 B3 (0.23 0.33 0.36 0.077 0)  
##                          3758) reimbursement2008>=5860 25   13 B2 (0.2 0.48 0.24 0.08 0)  
##                            7516) reimbursement2008< 19195 18    8 B2 (0.22 0.56 0.17 0.056 0) *
##                            7517) reimbursement2008>=19195 7    4 B3 (0.14 0.29 0.43 0.14 0) *
##                          3759) reimbursement2008< 5860 14    6 B3 (0.29 0.071 0.57 0.071 0) *
##                   235) age>=82.5 57   33 B1 (0.42 0.26 0.23 0.088 0)  
##                     470) cancer< 0.5 46   24 B1 (0.48 0.2 0.22 0.11 0)  
##                       940) age>=91.5 13    3 B1 (0.77 0.15 0.077 0 0) *
##                       941) age< 91.5 33   21 B1 (0.36 0.21 0.27 0.15 0)  
##                        1882) kidney< 0.5 26   15 B1 (0.42 0.19 0.19 0.19 0) *
##                        1883) kidney>=0.5 7    3 B3 (0.14 0.29 0.57 0 0) *
##                     471) cancer>=0.5 11    5 B2 (0.18 0.55 0.27 0 0) *
##                59) copd>=0.5 107   61 B2 (0.21 0.43 0.28 0.084 0)  
##                 118) reimbursement2008>=25420 13    7 B3 (0.31 0.23 0.46 0 0) *
##                 119) reimbursement2008< 25420 94   51 B2 (0.19 0.46 0.26 0.096 0)  
##                   238) reimbursement2008>=17845 8    1 B2 (0 0.88 0 0.12 0) *
##                   239) reimbursement2008< 17845 86   50 B2 (0.21 0.42 0.28 0.093 0)  
##                     478) reimbursement2008< 15470 79   44 B2 (0.19 0.44 0.29 0.076 0)  
##                       956) age< 75.5 41   25 B2 (0.27 0.39 0.24 0.098 0)  
##                        1912) osteoporosis< 0.5 30   19 B1 (0.37 0.37 0.17 0.1 0)  
##                          3824) age>=68.5 15    7 B1 (0.53 0.27 0.2 0 0) *
##                          3825) age< 68.5 15    8 B2 (0.2 0.47 0.13 0.2 0) *
##                        1913) osteoporosis>=0.5 11    6 B2 (0 0.45 0.45 0.091 0) *
##                       957) age>=75.5 38   19 B2 (0.11 0.5 0.34 0.053 0)  
##                        1914) reimbursement2008>=4300 31   13 B2 (0.097 0.58 0.26 0.065 0) *
##                        1915) reimbursement2008< 4300 7    2 B3 (0.14 0.14 0.71 0 0) *
##                     479) reimbursement2008>=15470 7    4 B1 (0.43 0.14 0.14 0.29 0) *
##            15) diabetes>=0.5 3594 2105 B2 (0.21 0.41 0.21 0.14 0.021)  
##              30) kidney< 0.5 1568  880 B2 (0.29 0.44 0.19 0.075 0.007)  
##                60) arthritis< 0.5 964  571 B2 (0.34 0.41 0.19 0.062 0.0052)  
##                 120) cancer< 0.5 791  473 B2 (0.37 0.4 0.16 0.061 0.0051)  
##                   240) age< 70.5 277  163 B1 (0.41 0.33 0.19 0.069 0.0036)  
##                     480) reimbursement2008< 8845 199  109 B1 (0.45 0.36 0.16 0.025 0)  
##                       960) copd< 0.5 155   78 B1 (0.5 0.3 0.18 0.019 0)  
##                        1920) reimbursement2008>=6290 32   17 B1 (0.47 0.47 0.062 0 0)  
##                          3840) age< 57.5 8    3 B1 (0.62 0.25 0.12 0 0) *
##                          3841) age>=57.5 24   11 B2 (0.42 0.54 0.042 0 0)  
##                            7682) ihd< 0.5 7    3 B1 (0.57 0.43 0 0 0) *
##                            7683) ihd>=0.5 17    7 B2 (0.35 0.59 0.059 0 0) *
##                        1921) reimbursement2008< 6290 123   61 B1 (0.5 0.26 0.21 0.024 0)  
##                          3842) reimbursement2008>=5150 19    4 B1 (0.79 0.053 0.16 0 0) *
##                          3843) reimbursement2008< 5150 104   57 B1 (0.45 0.3 0.22 0.029 0)  
##                            7686) alzheimers< 0.5 76   37 B1 (0.51 0.22 0.24 0.026 0)  
##                             15372) osteoporosis>=0.5 20    6 B1 (0.7 0.15 0.1 0.05 0) *
##                             15373) osteoporosis< 0.5 56   31 B1 (0.45 0.25 0.29 0.018 0)  
##                               30746) reimbursement2008< 3745 17    6 B1 (0.65 0.24 0.12 0 0) *
##                               30747) reimbursement2008>=3745 39   25 B1 (0.36 0.26 0.36 0.026 0)  
##                                 61494) reimbursement2008>=4475 16   10 B1 (0.38 0.38 0.19 0.062 0) *
##                                 61495) reimbursement2008< 4475 23   12 B3 (0.35 0.17 0.48 0 0)  
##                                  122990) age< 59 10    5 B1 (0.5 0.2 0.3 0 0) *
##                                  122991) age>=59 13    5 B3 (0.23 0.15 0.62 0 0) *
##                            7687) alzheimers>=0.5 28   14 B2 (0.29 0.5 0.18 0.036 0) *
##                       961) copd>=0.5 44   19 B2 (0.3 0.57 0.091 0.045 0) *
##                     481) reimbursement2008>=8845 78   54 B1 (0.31 0.24 0.26 0.18 0.013)  
##                       962) reimbursement2008>=11475 52   36 B1 (0.31 0.31 0.17 0.19 0.019)  
##                        1924) copd< 0.5 31   19 B1 (0.39 0.35 0.065 0.16 0.032)  
##                          3848) age>=67.5 7    1 B1 (0.86 0.14 0 0 0) *
##                          3849) age< 67.5 24   14 B2 (0.25 0.42 0.083 0.21 0.042)  
##                            7698) osteoporosis>=0.5 9    5 B1 (0.44 0.22 0 0.22 0.11) *
##                            7699) osteoporosis< 0.5 15    7 B2 (0.13 0.53 0.13 0.2 0) *
##                        1925) copd>=0.5 21   14 B3 (0.19 0.24 0.33 0.24 0)  
##                          3850) age>=56.5 13    7 B3 (0.15 0.23 0.46 0.15 0) *
##                          3851) age< 56.5 8    5 B4 (0.25 0.25 0.12 0.38 0) *
##                       963) reimbursement2008< 11475 26   15 B3 (0.31 0.12 0.42 0.15 0)  
##                        1926) depression< 0.5 15    9 B1 (0.4 0.2 0.33 0.067 0) *
##                        1927) depression>=0.5 11    5 B3 (0.18 0 0.55 0.27 0) *
##                   241) age>=70.5 514  287 B2 (0.35 0.44 0.15 0.056 0.0058)  
##                     482) reimbursement2008>=5045 327  200 B1 (0.39 0.38 0.15 0.067 0.0092)  
##                       964) depression< 0.5 170   92 B1 (0.46 0.34 0.14 0.059 0.0059)  
##                        1928) age< 88.5 144   73 B1 (0.49 0.34 0.1 0.063 0)  
##                          3856) age>=73.5 117   56 B1 (0.52 0.3 0.11 0.068 0)  
##                            7712) reimbursement2008< 5335 11    3 B1 (0.73 0 0.18 0.091 0) *
##                            7713) reimbursement2008>=5335 106   53 B1 (0.5 0.33 0.1 0.066 0)  
##                             15426) reimbursement2008>=6040 85   39 B1 (0.54 0.33 0.12 0.012 0)  
##                               30852) reimbursement2008< 29020 76   32 B1 (0.58 0.32 0.11 0 0)  
##                                 61704) reimbursement2008>=8850 48   16 B1 (0.67 0.23 0.1 0 0) *
##                                 61705) reimbursement2008< 8850 28   15 B2 (0.43 0.46 0.11 0 0)  
##                                  123410) reimbursement2008< 6985 13    4 B1 (0.69 0.15 0.15 0 0) *
##                                  123411) reimbursement2008>=6985 15    4 B2 (0.2 0.73 0.067 0 0) *
##                               30853) reimbursement2008>=29020 9    5 B2 (0.22 0.44 0.22 0.11 0) *
##                             15427) reimbursement2008< 6040 21   14 B1 (0.33 0.33 0.048 0.29 0)  
##                               30854) alzheimers< 0.5 13    7 B1 (0.46 0.31 0.077 0.15 0) *
##                               30855) alzheimers>=0.5 8    4 B4 (0.12 0.38 0 0.5 0) *
##                          3857) age< 73.5 27   13 B2 (0.37 0.52 0.074 0.037 0)  
##                            7714) heart.failure>=0.5 13    6 B1 (0.54 0.38 0.077 0 0) *
##                            7715) heart.failure< 0.5 14    5 B2 (0.21 0.64 0.071 0.071 0) *
##                        1929) age>=88.5 26   17 B2 (0.27 0.35 0.31 0.038 0.038)  
##                          3858) age>=92.5 7    2 B2 (0.14 0.71 0.14 0 0) *
##                          3859) age< 92.5 19   12 B3 (0.32 0.21 0.37 0.053 0.053) *
##                       965) depression>=0.5 157   90 B2 (0.31 0.43 0.17 0.076 0.013)  
##                        1930) age>=88.5 28   13 B1 (0.54 0.32 0.036 0.071 0.036)  
##                          3860) age< 94.5 17    5 B1 (0.71 0.12 0.059 0.12 0) *
##                          3861) age>=94.5 11    4 B2 (0.27 0.64 0 0 0.091) *
##                        1931) age< 88.5 129   71 B2 (0.26 0.45 0.2 0.078 0.0078)  
##                          3862) alzheimers< 0.5 61   26 B2 (0.23 0.57 0.16 0.033 0)  
##                            7724) reimbursement2008>=14285 14    7 B1 (0.5 0.29 0.21 0 0) *
##                            7725) reimbursement2008< 14285 47   16 B2 (0.15 0.66 0.15 0.043 0)  
##                             15450) age< 81.5 26    5 B2 (0.12 0.81 0.077 0 0) *
##                             15451) age>=81.5 21   11 B2 (0.19 0.48 0.24 0.095 0)  
##                               30902) copd< 0.5 10    3 B2 (0.2 0.7 0 0.1 0) *
##                               30903) copd>=0.5 11    6 B3 (0.18 0.27 0.45 0.091 0) *
##                          3863) alzheimers>=0.5 68   45 B2 (0.29 0.34 0.24 0.12 0.015)  
##                            7726) reimbursement2008>=7090 49   30 B2 (0.31 0.39 0.14 0.14 0.02)  
##                             15452) stroke< 0.5 38   23 B1 (0.39 0.34 0.13 0.13 0)  
##                               30904) heart.failure>=0.5 26   13 B1 (0.5 0.27 0.12 0.12 0)  
##                                 61808) osteoporosis< 0.5 18    7 B1 (0.61 0.22 0 0.17 0) *
##                                 61809) osteoporosis>=0.5 8    5 B2 (0.25 0.38 0.38 0 0) *
##                               30905) heart.failure< 0.5 12    6 B2 (0.17 0.5 0.17 0.17 0) *
##                             15453) stroke>=0.5 11    5 B2 (0 0.55 0.18 0.18 0.091) *
##                            7727) reimbursement2008< 7090 19   10 B3 (0.26 0.21 0.47 0.053 0) *
##                     483) reimbursement2008< 5045 187   85 B2 (0.27 0.55 0.14 0.037 0)  
##                       966) age< 77.5 74   26 B2 (0.23 0.65 0.095 0.027 0)  
##                        1932) reimbursement2008< 4725 64   26 B2 (0.27 0.59 0.11 0.031 0)  
##                          3864) reimbursement2008< 4345 50   15 B2 (0.22 0.7 0.04 0.04 0) *
##                          3865) reimbursement2008>=4345 14    8 B1 (0.43 0.21 0.36 0 0) *
##                        1933) reimbursement2008>=4725 10    0 B2 (0 1 0 0 0) *
##                       967) age>=77.5 113   59 B2 (0.3 0.48 0.18 0.044 0)  
##                        1934) age< 78.5 9    3 B1 (0.67 0.11 0.22 0 0) *
##                        1935) age>=78.5 104   51 B2 (0.27 0.51 0.17 0.048 0)  
##                          3870) depression>=0.5 37   23 B1 (0.38 0.38 0.16 0.081 0)  
##                            7740) reimbursement2008< 4035 17    8 B1 (0.53 0.29 0.12 0.059 0) *
##                            7741) reimbursement2008>=4035 20   11 B2 (0.25 0.45 0.2 0.1 0)  
##                             15482) age>=86.5 7    4 B3 (0.29 0.29 0.43 0 0) *
##                             15483) age< 86.5 13    6 B2 (0.23 0.54 0.077 0.15 0) *
##                          3871) depression< 0.5 67   28 B2 (0.21 0.58 0.18 0.03 0) *
##                 121) cancer>=0.5 173   98 B2 (0.18 0.43 0.31 0.069 0.0058)  
##                   242) age>=82.5 39   12 B2 (0.1 0.69 0.15 0.026 0.026) *
##                   243) age< 82.5 134   86 B2 (0.21 0.36 0.35 0.082 0)  
##                     486) age>=55 120   74 B2 (0.21 0.38 0.32 0.092 0)  
##                       972) age< 59.5 8    1 B2 (0.12 0.88 0 0 0) *
##                       973) age>=59.5 112   73 B2 (0.21 0.35 0.34 0.098 0)  
##                        1946) age< 71.5 49   33 B1 (0.33 0.27 0.33 0.082 0)  
##                          3892) copd>=0.5 16    8 B1 (0.5 0.25 0.12 0.12 0) *
##                          3893) copd< 0.5 33   19 B3 (0.24 0.27 0.42 0.061 0)  
##                            7786) reimbursement2008< 5825 11    5 B1 (0.55 0.18 0.27 0 0) *
##                            7787) reimbursement2008>=5825 22   11 B3 (0.091 0.32 0.5 0.091 0)  
##                             15574) heart.failure< 0.5 8    4 B2 (0.12 0.5 0.25 0.12 0) *
##                             15575) heart.failure>=0.5 14    5 B3 (0.071 0.21 0.64 0.071 0) *
##                        1947) age>=71.5 63   37 B2 (0.13 0.41 0.35 0.11 0)  
##                          3894) depression< 0.5 33   19 B3 (0.21 0.27 0.42 0.091 0)  
##                            7788) alzheimers< 0.5 26   17 B2 (0.23 0.35 0.35 0.077 0)  
##                             15576) age>=76.5 16   10 B3 (0.31 0.31 0.38 0 0) *
##                             15577) age< 76.5 10    6 B2 (0.1 0.4 0.3 0.2 0) *
##                            7789) alzheimers>=0.5 7    2 B3 (0.14 0 0.71 0.14 0) *
##                          3895) depression>=0.5 30   13 B2 (0.033 0.57 0.27 0.13 0)  
##                            7790) age< 75.5 13    2 B2 (0 0.85 0.077 0.077 0) *
##                            7791) age>=75.5 17   10 B3 (0.059 0.35 0.41 0.18 0) *
##                     487) age< 55 14    5 B3 (0.21 0.14 0.64 0 0) *
##                61) arthritis>=0.5 604  309 B2 (0.21 0.49 0.2 0.094 0.0099)  
##                 122) reimbursement2008< 3875 69   22 B2 (0.14 0.68 0.13 0.043 0) *
##                 123) reimbursement2008>=3875 535  287 B2 (0.21 0.46 0.21 0.1 0.011)  
##                   246) depression< 0.5 282  149 B2 (0.24 0.47 0.16 0.12 0.014)  
##                     492) alzheimers< 0.5 183  102 B2 (0.28 0.44 0.13 0.13 0.022)  
##                       984) reimbursement2008>=11200 56   35 B1 (0.38 0.36 0.11 0.11 0.054)  
##                        1968) copd< 0.5 38   19 B1 (0.5 0.32 0.053 0.11 0.026)  
##                          3936) age>=67.5 30   13 B1 (0.57 0.33 0.033 0.033 0.033) *
##                          3937) age< 67.5 8    5 B4 (0.25 0.25 0.12 0.38 0) *
##                        1969) copd>=0.5 18   10 B2 (0.11 0.44 0.22 0.11 0.11) *
##                       985) reimbursement2008< 11200 127   66 B2 (0.24 0.48 0.13 0.13 0.0079)  
##                        1970) reimbursement2008< 6240 85   47 B2 (0.32 0.45 0.13 0.094 0.012)  
##                          3940) age< 80.5 59   29 B2 (0.32 0.51 0.1 0.051 0.017)  
##                            7880) reimbursement2008< 4180 7    2 B1 (0.71 0.14 0.14 0 0) *
##                            7881) reimbursement2008>=4180 52   23 B2 (0.27 0.56 0.096 0.058 0.019)  
##                             15762) reimbursement2008>=4955 32   18 B2 (0.38 0.44 0.094 0.062 0.031)  
##                               31524) ihd< 0.5 8    2 B1 (0.75 0.25 0 0 0) *
##                               31525) ihd>=0.5 24   12 B2 (0.25 0.5 0.12 0.083 0.042) *
##                             15763) reimbursement2008< 4955 20    5 B2 (0.1 0.75 0.1 0.05 0) *
##                          3941) age>=80.5 26   18 B1 (0.31 0.31 0.19 0.19 0)  
##                            7882) osteoporosis< 0.5 18   10 B1 (0.44 0.28 0.17 0.11 0) *
##                            7883) osteoporosis>=0.5 8    5 B2 (0 0.38 0.25 0.38 0) *
##                        1971) reimbursement2008>=6240 42   19 B2 (0.095 0.55 0.14 0.21 0)  
##                          3942) age>=67.5 32   11 B2 (0.031 0.66 0.12 0.19 0) *
##                          3943) age< 67.5 10    7 B1 (0.3 0.2 0.2 0.3 0) *
##                     493) alzheimers>=0.5 99   47 B2 (0.16 0.53 0.21 0.1 0)  
##                       986) age>=79.5 37   22 B2 (0.27 0.41 0.14 0.19 0)  
##                        1972) heart.failure< 0.5 16   10 B1 (0.38 0.38 0.25 0 0) *
##                        1973) heart.failure>=0.5 21   12 B2 (0.19 0.43 0.048 0.33 0)  
##                          3946) age>=87 10    4 B2 (0.2 0.6 0 0.2 0) *
##                          3947) age< 87 11    6 B4 (0.18 0.27 0.091 0.45 0) *
##                       987) age< 79.5 62   25 B2 (0.097 0.6 0.26 0.048 0)  
##                        1974) reimbursement2008>=9010 17    4 B2 (0.059 0.76 0.12 0.059 0) *
##                        1975) reimbursement2008< 9010 45   21 B2 (0.11 0.53 0.31 0.044 0)  
##                          3950) reimbursement2008< 5595 23    7 B2 (0.087 0.7 0.13 0.087 0) *
##                          3951) reimbursement2008>=5595 22   11 B3 (0.14 0.36 0.5 0 0)  
##                            7902) reimbursement2008>=6650 15    8 B2 (0.2 0.47 0.33 0 0) *
##                            7903) reimbursement2008< 6650 7    1 B3 (0 0.14 0.86 0 0) *
##                   247) depression>=0.5 253  138 B2 (0.18 0.45 0.27 0.083 0.0079)  
##                     494) age>=40.5 241  131 B2 (0.19 0.46 0.26 0.087 0.0083)  
##                       988) age< 54.5 16    5 B2 (0.19 0.69 0.12 0 0) *
##                       989) age>=54.5 225  126 B2 (0.19 0.44 0.27 0.093 0.0089)  
##                        1978) reimbursement2008< 39120 216  118 B2 (0.19 0.45 0.26 0.083 0.0093)  
##                          3956) reimbursement2008>=15105 52   22 B2 (0.15 0.58 0.19 0.077 0)  
##                            7912) reimbursement2008< 23850 30    8 B2 (0.1 0.73 0.067 0.1 0) *
##                            7913) reimbursement2008>=23850 22   14 B2 (0.23 0.36 0.36 0.045 0)  
##                             15826) age>=72.5 12    5 B2 (0.17 0.58 0.25 0 0) *
##                             15827) age< 72.5 10    5 B3 (0.3 0.1 0.5 0.1 0) *
##                          3957) reimbursement2008< 15105 164   96 B2 (0.21 0.41 0.28 0.085 0.012)  
##                            7914) alzheimers< 0.5 90   47 B2 (0.2 0.48 0.22 0.089 0.011)  
##                             15828) osteoporosis< 0.5 53   28 B2 (0.26 0.47 0.13 0.11 0.019)  
##                               31656) copd>=0.5 10    5 B1 (0.5 0.2 0.1 0.1 0.1) *
##                               31657) copd< 0.5 43   20 B2 (0.21 0.53 0.14 0.12 0)  
##                                 63314) reimbursement2008>=4140 36   15 B2 (0.22 0.58 0.14 0.056 0)  
##                                  126628) reimbursement2008< 5440 13    2 B2 (0.077 0.85 0.077 0 0) *
##                                  126629) reimbursement2008>=5440 23   13 B2 (0.3 0.43 0.17 0.087 0)  
##                                    253258) reimbursement2008< 5980 7    3 B1 (0.57 0.29 0 0.14 0) *
##                                    253259) reimbursement2008>=5980 16    8 B2 (0.19 0.5 0.25 0.062 0) *
##                                 63315) reimbursement2008< 4140 7    4 B4 (0.14 0.29 0.14 0.43 0) *
##                             15829) osteoporosis>=0.5 37   19 B2 (0.11 0.49 0.35 0.054 0)  
##                               31658) age>=74.5 15    4 B2 (0 0.73 0.2 0.067 0) *
##                               31659) age< 74.5 22   12 B3 (0.18 0.32 0.45 0.045 0) *
##                            7915) alzheimers>=0.5 74   48 B3 (0.22 0.34 0.35 0.081 0.014)  
##                             15830) age< 79.5 46   27 B2 (0.15 0.41 0.39 0.043 0)  
##                               31660) reimbursement2008< 5620 10    3 B2 (0.1 0.7 0.2 0 0) *
##                               31661) reimbursement2008>=5620 36   20 B3 (0.17 0.33 0.44 0.056 0)  
##                                 63322) reimbursement2008>=8035 21   11 B2 (0.19 0.48 0.24 0.095 0)  
##                                  126644) age< 67.5 9    6 B1 (0.33 0.22 0.33 0.11 0) *
##                                  126645) age>=67.5 12    4 B2 (0.083 0.67 0.17 0.083 0) *
##                                 63323) reimbursement2008< 8035 15    4 B3 (0.13 0.13 0.73 0 0) *
##                             15831) age>=79.5 28   19 B1 (0.32 0.21 0.29 0.14 0.036)  
##                               31662) age< 84.5 9    3 B1 (0.67 0 0.11 0.11 0.11) *
##                               31663) age>=84.5 19   12 B3 (0.16 0.32 0.37 0.16 0) *
##                        1979) reimbursement2008>=39120 9    5 B3 (0.11 0.11 0.44 0.33 0) *
##                     495) age< 40.5 12    5 B3 (0 0.42 0.58 0 0) *
##              31) kidney>=0.5 2026 1225 B2 (0.15 0.4 0.23 0.19 0.033)  
##                62) reimbursement2008< 15095 1090  627 B2 (0.18 0.42 0.24 0.14 0.021)  
##                 124) arthritis< 0.5 638  402 B2 (0.22 0.37 0.24 0.15 0.025)  
##                   248) age>=44.5 612  383 B2 (0.23 0.37 0.23 0.15 0.026)  
##                     496) reimbursement2008>=6575 346  226 B2 (0.25 0.35 0.21 0.16 0.029)  
##                       992) age>=85.5 67   45 B1 (0.33 0.27 0.31 0.06 0.03)  
##                        1984) osteoporosis< 0.5 43   25 B1 (0.42 0.21 0.28 0.047 0.047)  
##                          3968) reimbursement2008< 8495 11    3 B1 (0.73 0 0.27 0 0) *
##                          3969) reimbursement2008>=8495 32   22 B1 (0.31 0.28 0.28 0.062 0.062)  
##                            7938) age< 96.5 24   15 B3 (0.29 0.33 0.38 0 0)  
##                             15876) reimbursement2008>=13055 13    7 B1 (0.46 0.23 0.31 0 0) *
##                             15877) reimbursement2008< 13055 11    6 B2 (0.091 0.45 0.45 0 0) *
##                            7939) age>=96.5 8    5 B1 (0.38 0.12 0 0.25 0.25) *
##                        1985) osteoporosis>=0.5 24   15 B2 (0.17 0.38 0.38 0.083 0)  
##                          3970) reimbursement2008< 9045 8    2 B2 (0 0.75 0.25 0 0) *
##                          3971) reimbursement2008>=9045 16    9 B3 (0.25 0.19 0.44 0.12 0) *
##                       993) age< 85.5 279  177 B2 (0.24 0.37 0.18 0.19 0.029)  
##                        1986) reimbursement2008< 6780 11    5 B1 (0.55 0.091 0.091 0.27 0) *
##                        1987) reimbursement2008>=6780 268  167 B2 (0.22 0.38 0.18 0.19 0.03)  
##                          3974) age< 77.5 177  108 B2 (0.26 0.39 0.14 0.18 0.028)  
##                            7948) reimbursement2008< 14365 169  100 B2 (0.25 0.41 0.12 0.18 0.03)  
##                             15896) age>=75.5 24   13 B1 (0.46 0.25 0.042 0.21 0.042)  
##                               31792) copd< 0.5 10    3 B1 (0.7 0 0.1 0.1 0.1) *
##                               31793) copd>=0.5 14    8 B2 (0.29 0.43 0 0.29 0) *
##                             15897) age< 75.5 145   82 B2 (0.22 0.43 0.14 0.18 0.028)  
##                               31794) stroke>=0.5 18    7 B2 (0.11 0.61 0.22 0.056 0) *
##                               31795) stroke< 0.5 127   75 B2 (0.24 0.41 0.13 0.2 0.031)  
##                                 63590) age>=68.5 65   34 B2 (0.25 0.48 0.15 0.11 0.015)  
##                                  127180) reimbursement2008< 10335 39   25 B1 (0.36 0.36 0.18 0.1 0)  
##                                    254360) reimbursement2008>=9355 8    3 B1 (0.62 0 0.12 0.25 0) *
##                                    254361) reimbursement2008< 9355 31   17 B2 (0.29 0.45 0.19 0.065 0)  
##                                      508722) heart.failure< 0.5 9    4 B1 (0.56 0.22 0.22 0 0) *
##                                      508723) heart.failure>=0.5 22   10 B2 (0.18 0.55 0.18 0.091 0)  
##                                       1017446) age< 71.5 12    3 B2 (0.17 0.75 0 0.083 0) *
##                                       1017447) age>=71.5 10    6 B3 (0.2 0.3 0.4 0.1 0) *
##                                  127181) reimbursement2008>=10335 26    9 B2 (0.077 0.65 0.12 0.12 0.038) *
##                                 63591) age< 68.5 62   41 B2 (0.23 0.34 0.097 0.29 0.048)  
##                                  127182) reimbursement2008>=10290 28   18 B4 (0.32 0.21 0.071 0.36 0.036)  
##                                    254364) reimbursement2008< 10940 7    3 B1 (0.57 0 0.29 0.14 0) *
##                                    254365) reimbursement2008>=10940 21   12 B4 (0.24 0.29 0 0.43 0.048)  
##                                      508730) alzheimers< 0.5 13    8 B2 (0.23 0.38 0 0.31 0.077) *
##                                      508731) alzheimers>=0.5 8    3 B4 (0.25 0.12 0 0.62 0) *
##                                  127183) reimbursement2008< 10290 34   19 B2 (0.15 0.44 0.12 0.24 0.059)  
##                                    254366) age< 65.5 25   12 B2 (0.16 0.52 0.12 0.12 0.08) *
##                                    254367) age>=65.5 9    4 B4 (0.11 0.22 0.11 0.56 0) *
##                            7949) reimbursement2008>=14365 8    4 B3 (0.38 0 0.5 0.12 0) *
##                          3975) age>=77.5 91   59 B2 (0.15 0.35 0.26 0.2 0.033)  
##                            7950) alzheimers< 0.5 34   23 B3 (0.26 0.24 0.32 0.12 0.059)  
##                             15900) copd>=0.5 10    5 B2 (0.2 0.5 0.2 0 0.1) *
##                             15901) copd< 0.5 24   15 B3 (0.29 0.12 0.38 0.17 0.042)  
##                               31802) cancer< 0.5 17   10 B1 (0.41 0.12 0.29 0.12 0.059) *
##                               31803) cancer>=0.5 7    3 B3 (0 0.14 0.57 0.29 0) *
##                            7951) alzheimers>=0.5 57   33 B2 (0.088 0.42 0.23 0.25 0.018)  
##                             15902) reimbursement2008>=9695 38   18 B2 (0.079 0.53 0.26 0.13 0)  
##                               31804) reimbursement2008< 13070 23   10 B2 (0.087 0.57 0.35 0 0)  
##                                 63608) reimbursement2008< 11420 13    4 B2 (0.077 0.69 0.23 0 0) *
##                                 63609) reimbursement2008>=11420 10    5 B3 (0.1 0.4 0.5 0 0) *
##                               31805) reimbursement2008>=13070 15    8 B2 (0.067 0.47 0.13 0.33 0) *
##                             15903) reimbursement2008< 9695 19   10 B4 (0.11 0.21 0.16 0.47 0.053) *
##                     497) reimbursement2008< 6575 266  157 B2 (0.19 0.41 0.26 0.12 0.023)  
##                       994) age>=92.5 19    5 B2 (0.16 0.74 0.053 0.053 0) *
##                       995) age< 92.5 247  152 B2 (0.19 0.38 0.27 0.13 0.024)  
##                        1990) age< 88.5 235  142 B2 (0.19 0.4 0.25 0.14 0.026)  
##                          3980) reimbursement2008< 6170 210  127 B2 (0.21 0.4 0.22 0.15 0.024)  
##                            7960) age>=81.5 48   23 B2 (0.19 0.52 0.15 0.12 0.021)  
##                             15920) depression< 0.5 25   15 B2 (0.32 0.4 0.12 0.12 0.04)  
##                               31840) alzheimers>=0.5 12    5 B1 (0.58 0.17 0.083 0.17 0) *
##                               31841) alzheimers< 0.5 13    5 B2 (0.077 0.62 0.15 0.077 0.077) *
##                             15921) depression>=0.5 23    8 B2 (0.043 0.65 0.17 0.13 0) *
##                            7961) age< 81.5 162  104 B2 (0.22 0.36 0.25 0.15 0.025)  
##                             15922) reimbursement2008< 4895 94   54 B2 (0.23 0.43 0.18 0.14 0.021)  
##                               31844) reimbursement2008< 4080 47   32 B1 (0.32 0.3 0.21 0.13 0.043)  
##                                 63688) age< 60.5 7    2 B2 (0.14 0.71 0.14 0 0) *
##                                 63689) age>=60.5 40   26 B1 (0.35 0.23 0.23 0.15 0.05)  
##                                  127378) age< 71.5 14    6 B1 (0.57 0.21 0.071 0.14 0) *
##                                  127379) age>=71.5 26   18 B3 (0.23 0.23 0.31 0.15 0.077)  
##                                    254758) reimbursement2008< 3885 19   13 B1 (0.32 0.21 0.21 0.16 0.11) *
##                                    254759) reimbursement2008>=3885 7    3 B3 (0 0.29 0.57 0.14 0) *
##                               31845) reimbursement2008>=4080 47   21 B2 (0.15 0.55 0.15 0.15 0) *
##                             15923) reimbursement2008>=4895 68   45 B3 (0.19 0.26 0.34 0.18 0.029)  
##                               31846) alzheimers< 0.5 39   27 B2 (0.28 0.31 0.23 0.15 0.026)  
##                                 63692) age>=76.5 15    9 B3 (0.27 0.33 0.4 0 0) *
##                                 63693) age< 76.5 24   17 B1 (0.29 0.29 0.12 0.25 0.042)  
##                                  127386) depression>=0.5 14    8 B2 (0.36 0.43 0.071 0.071 0.071) *
##                                  127387) depression< 0.5 10    5 B4 (0.2 0.1 0.2 0.5 0) *
##                               31847) alzheimers>=0.5 29   15 B3 (0.069 0.21 0.48 0.21 0.034) *
##                          3981) reimbursement2008>=6170 25   13 B3 (0.04 0.4 0.48 0.04 0.04)  
##                            7962) reimbursement2008>=6260 17    8 B2 (0 0.53 0.41 0 0.059) *
##                            7963) reimbursement2008< 6260 8    3 B3 (0.12 0.12 0.62 0.12 0) *
##                        1991) age>=88.5 12    4 B3 (0.17 0.17 0.67 0 0) *
##                   249) age< 44.5 26   11 B3 (0.038 0.27 0.58 0.12 0)  
##                     498) age< 34 7    3 B2 (0 0.57 0.43 0 0) *
##                     499) age>=34 19    7 B3 (0.053 0.16 0.63 0.16 0) *
##                 125) arthritis>=0.5 452  225 B2 (0.12 0.5 0.24 0.12 0.015)  
##                   250) reimbursement2008< 5300 143   58 B2 (0.14 0.59 0.15 0.1 0.007)  
##                     500) reimbursement2008>=5155 11    1 B2 (0 0.91 0 0.091 0) *
##                     501) reimbursement2008< 5155 132   57 B2 (0.15 0.57 0.17 0.11 0.0076)  
##                      1002) reimbursement2008< 4815 107   42 B2 (0.15 0.61 0.14 0.093 0.0093)  
##                        2004) reimbursement2008< 4595 88   38 B2 (0.18 0.57 0.16 0.08 0.011)  
##                          4008) reimbursement2008< 3725 19    5 B2 (0.11 0.74 0.053 0.11 0) *
##                          4009) reimbursement2008>=3725 69   33 B2 (0.2 0.52 0.19 0.072 0.014)  
##                            8018) osteoporosis>=0.5 29   15 B2 (0.34 0.48 0.1 0.069 0)  
##                             16036) reimbursement2008< 4270 22   10 B2 (0.41 0.55 0.045 0 0)  
##                               32072) reimbursement2008< 3905 7    3 B1 (0.57 0.29 0.14 0 0) *
##                               32073) reimbursement2008>=3905 15    5 B2 (0.33 0.67 0 0 0) *
##                             16037) reimbursement2008>=4270 7    5 B2 (0.14 0.29 0.29 0.29 0) *
##                            8019) osteoporosis< 0.5 40   18 B2 (0.1 0.55 0.25 0.075 0.025)  
##                             16038) reimbursement2008>=3995 31   11 B2 (0.097 0.65 0.16 0.065 0.032) *
##                             16039) reimbursement2008< 3995 9    4 B3 (0.11 0.22 0.56 0.11 0) *
##                        2005) reimbursement2008>=4595 19    4 B2 (0 0.79 0.053 0.16 0) *
##                      1003) reimbursement2008>=4815 25   15 B2 (0.16 0.4 0.28 0.16 0)  
##                        2006) reimbursement2008>=4975 16    8 B2 (0.19 0.5 0.19 0.12 0) *
##                        2007) reimbursement2008< 4975 9    5 B3 (0.11 0.22 0.44 0.22 0) *
##                   251) reimbursement2008>=5300 309  167 B2 (0.12 0.46 0.28 0.13 0.019)  
##                     502) ihd< 0.5 24   16 B3 (0.29 0.29 0.33 0.083 0)  
##                      1004) age>=70 16   10 B1 (0.38 0.31 0.19 0.12 0) *
##                      1005) age< 70 8    3 B3 (0.12 0.25 0.62 0 0) *
##                     503) ihd>=0.5 285  150 B2 (0.1 0.47 0.27 0.13 0.021)  
##                      1006) reimbursement2008>=5725 253  138 B2 (0.11 0.45 0.27 0.14 0.02)  
##                        2012) reimbursement2008< 6565 35   23 B3 (0.2 0.31 0.34 0.14 0)  
##                          4024) age< 72.5 13    7 B2 (0.23 0.46 0.15 0.15 0) *
##                          4025) age>=72.5 22   12 B3 (0.18 0.23 0.45 0.14 0) *
##                        2013) reimbursement2008>=6565 218  114 B2 (0.1 0.48 0.26 0.14 0.023)  
##                          4026) reimbursement2008>=7265 187  100 B2 (0.11 0.47 0.28 0.12 0.027)  
##                            8052) heart.failure< 0.5 35   21 B2 (0.2 0.4 0.2 0.17 0.029) *
##                            8053) heart.failure>=0.5 152   79 B2 (0.086 0.48 0.3 0.11 0.026)  
##                             16106) reimbursement2008< 13595 130   65 B2 (0.1 0.5 0.28 0.11 0.015)  
##                               32212) reimbursement2008>=10630 52   24 B2 (0.15 0.54 0.19 0.096 0.019)  
##                                 64424) reimbursement2008< 11260 14    2 B2 (0.071 0.86 0.071 0 0) *
##                                 64425) reimbursement2008>=11260 38   22 B2 (0.18 0.42 0.24 0.13 0.026)  
##                                  128850) alzheimers>=0.5 25   12 B2 (0.2 0.52 0.12 0.12 0.04) *
##                                  128851) alzheimers< 0.5 13    7 B3 (0.15 0.23 0.46 0.15 0) *
##                               32213) reimbursement2008< 10630 78   41 B2 (0.064 0.47 0.33 0.12 0.013)  
##                                 64426) depression< 0.5 37   17 B2 (0.081 0.54 0.27 0.11 0) *
##                                 64427) depression>=0.5 41   24 B2 (0.049 0.41 0.39 0.12 0.024)  
##                                  128854) reimbursement2008< 10175 34   18 B2 (0.029 0.47 0.35 0.12 0.029)  
##                                    257708) reimbursement2008>=9480 7    2 B2 (0 0.71 0.14 0.14 0) *
##                                    257709) reimbursement2008< 9480 27   16 B2 (0.037 0.41 0.41 0.11 0.037)  
##                                      515418) reimbursement2008< 9020 19   10 B2 (0.053 0.47 0.26 0.16 0.053) *
##                                      515419) reimbursement2008>=9020 8    2 B3 (0 0.25 0.75 0 0) *
##                                  128855) reimbursement2008>=10175 7    3 B3 (0.14 0.14 0.57 0.14 0) *
##                             16107) reimbursement2008>=13595 22   12 B3 (0 0.36 0.45 0.091 0.091)  
##                               32214) reimbursement2008>=14005 14    7 B2 (0 0.5 0.36 0 0.14) *
##                               32215) reimbursement2008< 14005 8    3 B3 (0 0.12 0.62 0.25 0) *
##                          4027) reimbursement2008< 7265 31   14 B2 (0.065 0.55 0.13 0.26 0) *
##                      1007) reimbursement2008< 5725 32   12 B2 (0 0.62 0.25 0.094 0.031)  
##                        2014) reimbursement2008>=5385 22    5 B2 (0 0.77 0.18 0 0.045) *
##                        2015) reimbursement2008< 5385 10    6 B3 (0 0.3 0.4 0.3 0) *
##                63) reimbursement2008>=15095 936  598 B2 (0.13 0.36 0.22 0.24 0.046)  
##                 126) ihd< 0.5 53   35 B2 (0.3 0.34 0.075 0.26 0.019)  
##                   252) reimbursement2008>=25800 20    9 B1 (0.55 0.25 0.05 0.15 0)  
##                     504) age< 79.5 11    2 B1 (0.82 0 0.091 0.091 0) *
##                     505) age>=79.5 9    4 B2 (0.22 0.56 0 0.22 0) *
##                   253) reimbursement2008< 25800 33   20 B2 (0.15 0.39 0.091 0.33 0.03)  
##                     506) age< 79.5 20    8 B2 (0.05 0.6 0.1 0.2 0.05)  
##                      1012) reimbursement2008< 22825 13    2 B2 (0.077 0.85 0 0 0.077) *
##                      1013) reimbursement2008>=22825 7    3 B4 (0 0.14 0.29 0.57 0) *
##                     507) age>=79.5 13    6 B4 (0.31 0.077 0.077 0.54 0) *
##                 127) ihd>=0.5 883  563 B2 (0.12 0.36 0.23 0.24 0.048)  
##                   254) reimbursement2008< 26375 396  261 B2 (0.17 0.34 0.25 0.2 0.043)  
##                     508) arthritis< 0.5 233  160 B2 (0.21 0.31 0.21 0.24 0.034)  
##                      1016) copd< 0.5 95   68 B1 (0.28 0.24 0.21 0.26 0)  
##                        2032) reimbursement2008>=18065 67   45 B1 (0.33 0.18 0.25 0.24 0)  
##                          4064) reimbursement2008>=18390 59   39 B1 (0.34 0.2 0.2 0.25 0)  
##                            8128) stroke>=0.5 10    5 B2 (0.4 0.5 0.1 0 0) *
##                            8129) stroke< 0.5 49   33 B1 (0.33 0.14 0.22 0.31 0)  
##                             16258) age< 86.5 41   26 B1 (0.37 0.17 0.22 0.24 0)  
##                               32516) depression>=0.5 23   11 B1 (0.52 0.087 0.13 0.26 0) *
##                               32517) depression< 0.5 18   12 B3 (0.17 0.28 0.33 0.22 0) *
##                             16259) age>=86.5 8    3 B4 (0.12 0 0.25 0.62 0) *
##                          4065) reimbursement2008< 18390 8    3 B3 (0.25 0 0.62 0.12 0) *
##                        2033) reimbursement2008< 18065 28   17 B2 (0.18 0.39 0.11 0.32 0)  
##                          4066) reimbursement2008< 16540 9    6 B1 (0.33 0.11 0.33 0.22 0) *
##                          4067) reimbursement2008>=16540 19    9 B2 (0.11 0.53 0 0.37 0) *
##                      1017) copd>=0.5 138   88 B2 (0.15 0.36 0.21 0.22 0.058)  
##                        2034) reimbursement2008>=22770 41   21 B2 (0.17 0.49 0.15 0.098 0.098)  
##                          4068) age< 83.5 32   13 B2 (0.12 0.59 0.12 0.094 0.062)  
##                            8136) reimbursement2008>=25510 7    4 B1 (0.43 0.14 0.14 0.29 0) *
##                            8137) reimbursement2008< 25510 25    7 B2 (0.04 0.72 0.12 0.04 0.08) *
##                          4069) age>=83.5 9    6 B1 (0.33 0.11 0.22 0.11 0.22) *
##                        2035) reimbursement2008< 22770 97   67 B2 (0.14 0.31 0.24 0.27 0.041)  
##                          4070) reimbursement2008< 21150 81   53 B2 (0.17 0.35 0.22 0.22 0.037)  
##                            8140) age< 73.5 35   18 B2 (0.14 0.49 0.17 0.14 0.057)  
##                             16280) age>=60 28   12 B2 (0.18 0.57 0.11 0.11 0.036) *
##                             16281) age< 60 7    4 B3 (0 0.14 0.43 0.29 0.14) *
##                            8141) age>=73.5 46   33 B4 (0.2 0.24 0.26 0.28 0.022)  
##                             16282) age>=75.5 39   28 B2 (0.23 0.28 0.23 0.23 0.026)  
##                               32564) age< 80 10    5 B3 (0.2 0.3 0.5 0 0) *
##                               32565) age>=80 29   20 B4 (0.24 0.28 0.14 0.31 0.034)  
##                                 65130) age>=83.5 22   14 B2 (0.27 0.36 0.14 0.23 0)  
##                                  130260) reimbursement2008>=17685 10    6 B1 (0.4 0.3 0.2 0.1 0) *
##                                  130261) reimbursement2008< 17685 12    7 B2 (0.17 0.42 0.083 0.33 0) *
##                                 65131) age< 83.5 7    3 B4 (0.14 0 0.14 0.57 0.14) *
##                             16283) age< 75.5 7    3 B4 (0 0 0.43 0.57 0) *
##                          4071) reimbursement2008>=21150 16    8 B4 (0 0.12 0.31 0.5 0.062) *
##                     509) arthritis>=0.5 163  101 B2 (0.11 0.38 0.31 0.15 0.055)  
##                      1018) heart.failure>=0.5 140   83 B2 (0.12 0.41 0.27 0.14 0.057)  
##                        2036) age>=65 125   71 B2 (0.14 0.43 0.26 0.13 0.048)  
##                          4072) reimbursement2008>=22510 36   19 B2 (0.11 0.47 0.36 0 0.056)  
##                            8144) reimbursement2008>=22930 29   13 B2 (0.1 0.55 0.31 0 0.034)  
##                             16288) age< 86 22    8 B2 (0.091 0.64 0.27 0 0) *
##                             16289) age>=86 7    4 B3 (0.14 0.29 0.43 0 0.14) *
##                            8145) reimbursement2008< 22930 7    3 B3 (0.14 0.14 0.57 0 0.14) *
##                          4073) reimbursement2008< 22510 89   52 B2 (0.15 0.42 0.21 0.18 0.045)  
##                            8146) reimbursement2008>=17640 55   33 B2 (0.24 0.4 0.16 0.16 0.036)  
##                             16292) reimbursement2008< 18970 20   11 B1 (0.45 0.2 0.2 0.15 0)  
##                               32584) depression>=0.5 10    6 B2 (0.3 0.4 0.3 0 0) *
##                               32585) depression< 0.5 10    4 B1 (0.6 0 0.1 0.3 0) *
##                             16293) reimbursement2008>=18970 35   17 B2 (0.11 0.51 0.14 0.17 0.057) *
##                            8147) reimbursement2008< 17640 34   19 B2 (0 0.44 0.29 0.21 0.059)  
##                             16294) age< 77 9    2 B2 (0 0.78 0.22 0 0) *
##                             16295) age>=77 25   17 B2 (0 0.32 0.32 0.28 0.08)  
##                               32590) age< 82.5 10    5 B3 (0 0.3 0.5 0.1 0.1) *
##                               32591) age>=82.5 15    9 B4 (0 0.33 0.2 0.4 0.067) *
##                        2037) age< 65 15    9 B3 (0 0.2 0.4 0.27 0.13) *
##                      1019) heart.failure< 0.5 23   11 B3 (0.043 0.22 0.52 0.17 0.043)  
##                        2038) copd< 0.5 13    8 B2 (0.077 0.38 0.23 0.23 0.077) *
##                        2039) copd>=0.5 10    1 B3 (0 0 0.9 0.1 0) *
##                   255) reimbursement2008>=26375 487  302 B2 (0.076 0.38 0.21 0.28 0.051)  
##                     510) age>=88.5 65   28 B2 (0.11 0.57 0.11 0.15 0.062) *
##                     511) age< 88.5 422  274 B2 (0.071 0.35 0.23 0.3 0.05)  
##                      1022) reimbursement2008< 32040 91   47 B2 (0.066 0.48 0.19 0.23 0.033)  
##                        2044) age>=72 47   22 B2 (0.064 0.53 0.21 0.13 0.064)  
##                          4088) osteoporosis< 0.5 30   10 B2 (0.067 0.67 0.067 0.13 0.067) *
##                          4089) osteoporosis>=0.5 17    9 B3 (0.059 0.29 0.47 0.12 0.059) *
##                        2045) age< 72 44   25 B2 (0.068 0.43 0.16 0.34 0)  
##                          4090) alzheimers< 0.5 11    4 B2 (0.091 0.64 0.18 0.091 0) *
##                          4091) alzheimers>=0.5 33   19 B4 (0.061 0.36 0.15 0.42 0)  
##                            8182) arthritis>=0.5 17    8 B2 (0 0.53 0.059 0.41 0) *
##                            8183) arthritis< 0.5 16    9 B4 (0.12 0.19 0.25 0.44 0) *
##                      1023) reimbursement2008>=32040 331  226 B4 (0.073 0.31 0.24 0.32 0.054)  
##                        2046) stroke>=0.5 97   58 B2 (0.062 0.4 0.18 0.29 0.072)  
##                          4092) copd< 0.5 26   17 B2 (0.23 0.35 0.19 0.19 0.038)  
##                            8184) depression< 0.5 13    7 B1 (0.46 0.15 0.15 0.15 0.077) *
##                            8185) depression>=0.5 13    6 B2 (0 0.54 0.23 0.23 0) *
##                          4093) copd>=0.5 71   41 B2 (0 0.42 0.17 0.32 0.085)  
##                            8186) reimbursement2008< 38625 13    7 B2 (0 0.46 0.38 0.077 0.077) *
##                            8187) reimbursement2008>=38625 58   34 B2 (0 0.41 0.12 0.38 0.086)  
##                             16374) age< 79.5 39   20 B2 (0 0.49 0.077 0.44 0)  
##                               32748) age>=63.5 26   12 B2 (0 0.54 0.12 0.35 0) *
##                               32749) age< 63.5 13    5 B4 (0 0.38 0 0.62 0) *
##                             16375) age>=79.5 19   14 B2 (0 0.26 0.21 0.26 0.26) *
##                        2047) stroke< 0.5 234  157 B4 (0.077 0.28 0.27 0.33 0.047)  
##                          4094) reimbursement2008>=37290 180  126 B2 (0.078 0.3 0.29 0.28 0.044)  
##                            8188) age< 82.5 150  101 B2 (0.093 0.33 0.28 0.25 0.047)  
##                             16376) reimbursement2008< 88685 139   91 B2 (0.1 0.35 0.26 0.26 0.036)  
##                               32752) reimbursement2008>=79435 7    2 B2 (0 0.71 0 0.29 0) *
##                               32753) reimbursement2008< 79435 132   89 B2 (0.11 0.33 0.27 0.26 0.038)  
##                                 65506) age>=68.5 72   48 B2 (0.15 0.33 0.19 0.28 0.042)  
##                                  131012) heart.failure>=0.5 65   41 B2 (0.14 0.37 0.2 0.25 0.046)  
##                                    262024) age>=72.5 46   27 B2 (0.11 0.41 0.24 0.17 0.065)  
##                                      524048) reimbursement2008>=52775 25   16 B2 (0.16 0.36 0.36 0.08 0.04)  
##                                       1048096) reimbursement2008>=59785 11    7 B1 (0.36 0.36 0.091 0.18 0) *
##                                       1048097) reimbursement2008< 59785 14    6 B3 (0 0.36 0.57 0 0.071) *
##                                      524049) reimbursement2008< 52775 21   11 B2 (0.048 0.48 0.095 0.29 0.095)  
##                                       1048098) copd< 0.5 7    1 B2 (0 0.86 0 0.14 0) *
##                                       1048099) copd>=0.5 14    9 B4 (0.071 0.29 0.14 0.36 0.14) *
##                                    262025) age< 72.5 19   11 B4 (0.21 0.26 0.11 0.42 0) *
##                                  131013) heart.failure< 0.5 7    3 B4 (0.29 0 0.14 0.57 0) *
##                                 65507) age< 68.5 60   38 B3 (0.05 0.32 0.37 0.23 0.033)  
##                                  131014) osteoporosis< 0.5 38   20 B3 (0.053 0.26 0.47 0.18 0.026)  
##                                    262028) reimbursement2008< 44435 16    6 B3 (0.12 0.12 0.62 0.12 0) *
##                                    262029) reimbursement2008>=44435 22   14 B2 (0 0.36 0.36 0.23 0.045)  
##                                      524058) depression>=0.5 12    6 B2 (0 0.5 0.17 0.25 0.083) *
##                                      524059) depression< 0.5 10    4 B3 (0 0.2 0.6 0.2 0) *
##                                  131015) osteoporosis>=0.5 22   13 B2 (0.045 0.41 0.18 0.32 0.045)  
##                                    262030) depression< 0.5 8    3 B2 (0.12 0.62 0.12 0.12 0) *
##                                    262031) depression>=0.5 14    8 B4 (0 0.29 0.21 0.43 0.071) *
##                             16377) reimbursement2008>=88685 11    5 B3 (0 0.091 0.55 0.18 0.18) *
##                            8189) age>=82.5 30   17 B4 (0 0.17 0.37 0.43 0.033)  
##                             16378) copd< 0.5 9    5 B3 (0 0.22 0.44 0.22 0.11) *
##                             16379) copd>=0.5 21   10 B4 (0 0.14 0.33 0.52 0)  
##                               32758) depression>=0.5 10    5 B3 (0 0.1 0.5 0.4 0) *
##                               32759) depression< 0.5 11    4 B4 (0 0.18 0.18 0.64 0) *
##                          4095) reimbursement2008< 37290 54   28 B4 (0.074 0.2 0.19 0.48 0.056)  
##                            8190) reimbursement2008< 35865 39   25 B4 (0.1 0.26 0.21 0.36 0.077)  
##                             16380) depression>=0.5 27   19 B2 (0.074 0.3 0.3 0.3 0.037)  
##                               32760) age>=70 19   12 B3 (0.11 0.32 0.37 0.21 0) *
##                               32761) age< 70 8    4 B4 (0 0.25 0.12 0.5 0.12) *
##                             16381) depression< 0.5 12    6 B4 (0.17 0.17 0 0.5 0.17) *
##                            8191) reimbursement2008>=35865 15    3 B4 (0 0.067 0.13 0.8 0) *
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12588   654   148    36     0
##        B2  1419  2122   203    59     0
##        B3   767   486   488    48     0
##        B4   336   279    99   153     0
##        B5    41    49    15    10     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.675500e-01   4.861839e-01   7.616324e-01   7.733898e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##  3.187284e-196  1.002543e-280 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 11972  1166   232    56     0
##        B2  1955  1384   367    98     0
##        B3   889   657   183    60     0
##        B4   346   349   114    57     0
##        B5    39    48    18    10     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   6.798000e-01   2.897201e-01   6.732832e-01   6.862645e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   5.289133e-03  1.795989e-240 
##                      model_id model_method
## 1 All.X.lser.ys.cp.4015.rpart        rpart
##                                                                                                                                             feats
## 1 age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
##   max.nTuningRuns min.elapsedtime.everything min.elapsedtime.final
## 1               1                      5.857                 0.916
##   max.Accuracy.fit max.AccuracyLower.fit max.AccuracyUpper.fit
## 1          0.76755             0.7616324             0.7733898
##   max.Kappa.fit min.loss.error.fit max.Accuracy.OOB max.AccuracyLower.OOB
## 1     0.4861839          0.7723494           0.6798             0.6732832
##   max.AccuracyUpper.OOB max.Kappa.OOB min.loss.error.OOB min.SSE.fit
## 1             0.6862645     0.2897201            0.77965           0
##   min.loss.errorSD.fit
## 1           0.01641269
# Simplify a model
# fit_df <- glb_entity_df; glb_mdl <- step(<complex>_mdl)

print(glb_models_df)
##                       model_id     model_method
## 1    Baseline.mybaseln_classfr mybaseln_classfr
## 2            MFO.myMFO_classfr    myMFO_classfr
## 3      Random.myrandom_classfr myrandom_classfr
## 4         Max.cor.Y.cv.0.rpart            rpart
## 5         Max.cor.Y.cv.G.rpart            rpart
## 6    Interact.High.cor.y.rpart            rpart
## 7              Low.cor.X.rpart            rpart
## 8   All.X.lser.no.cp.opt.rpart            rpart
## 9  All.X.lser.no.cp.4015.rpart            rpart
## 10  All.X.lser.ys.cp.opt.rpart            rpart
## 11 All.X.lser.ys.cp.4015.rpart            rpart
##                                                                                                                                              feats
## 1                                                                                                                          bucket2008.fctr, .rnorm
## 2                                                                                                                                           .rnorm
## 3                                                                                                                                           .rnorm
## 4                                                                                                                                       bucket2008
## 5                                                                                                                                       bucket2008
## 6                                                                                                                    bucket2008, reimbursement2008
## 7                     bucket2008, diabetes, ihd, kidney, heart.failure, copd, depression, alzheimers, arthritis, osteoporosis, cancer, stroke, age
## 8  age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
## 9  age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
## 10 age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
## 11 age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
##    max.nTuningRuns min.elapsedtime.everything min.elapsedtime.final
## 1                0                      0.425                 0.003
## 2                0                      0.258                 0.005
## 3                0                      0.231                 0.003
## 4                0                      0.779                 0.248
## 5                3                      2.316                 0.246
## 6                3                      2.997                 0.361
## 7                3                      6.536                 0.866
## 8                3                      6.806                 0.919
## 9                1                      5.426                 0.914
## 10               3                      7.386                 0.917
## 11               1                      5.857                 0.916
##    max.Accuracy.fit max.AccuracyLower.fit max.AccuracyUpper.fit
## 1         0.6807000             0.6741879             0.6871595
## 2         0.6713000             0.6647403             0.6778099
## 3         0.4978000             0.4908463             0.5047543
## 4         0.6713000             0.6647403             0.6778099
## 5         0.7015991             0.6952047             0.7079366
## 6         0.6964492             0.6956574             0.7083838
## 7         0.7092992             0.7024989             0.7151403
## 8         0.7074489             0.7012915             0.7139481
## 9         0.6782992             0.7616324             0.7733898
## 10        0.7020500             0.6956574             0.7083838
## 11        0.7675500             0.7616324             0.7733898
##    max.Kappa.fit max.Accuracy.OOB max.AccuracyLower.OOB
## 1   3.150835e-01          0.68525             0.6787621
## 2   0.000000e+00          0.67130             0.6647403
## 3  -7.473179e-05          0.49900             0.4920461
## 4   0.000000e+00          0.67130             0.6647403
## 5   3.390926e-01          0.70440             0.6980216
## 6   3.134828e-01          0.70585             0.6994804
## 7   3.218867e-01          0.70680             0.7004362
## 8   3.038255e-01          0.70720             0.7008387
## 9   2.927210e-01          0.67980             0.6732832
## 10  3.217129e-01          0.70585             0.6994804
## 11  4.861839e-01          0.67980             0.6732832
##    max.AccuracyUpper.OOB max.Kappa.OOB min.SSE.fit max.AccuracySD.fit
## 1              0.6916841   0.322963052           0                 NA
## 2              0.6778099   0.000000000           0                 NA
## 3              0.5059542   0.003477783           0                 NA
## 4              0.6778099   0.000000000           0                 NA
## 5              0.7107190   0.343510796           0        0.004432663
## 6              0.7121597   0.328654953           0        0.004645926
## 7              0.7131036   0.306927409           0        0.005333283
## 8              0.7135010   0.294269180           0        0.006818137
## 9              0.6862645   0.289720052           0        0.006853054
## 10             0.7121597   0.328654953           0                 NA
## 11             0.6862645   0.289720052           0                 NA
##    max.KappaSD.fit min.loss.error.fit min.loss.error.OOB
## 1               NA                 NA                 NA
## 2               NA                 NA                 NA
## 3               NA                 NA                 NA
## 4               NA                 NA                 NA
## 5      0.007882575                 NA                 NA
## 6      0.013637821                 NA                 NA
## 7      0.012387416                 NA                 NA
## 8      0.020611981                 NA                 NA
## 9      0.014553753                 NA                 NA
## 10              NA          0.7768504            0.76180
## 11              NA          0.7723494            0.77965
##    min.loss.errorSD.fit
## 1                    NA
## 2                    NA
## 3                    NA
## 4                    NA
## 5                    NA
## 6                    NA
## 7                    NA
## 8                    NA
## 9                    NA
## 10           0.01485311
## 11           0.01641269
if (!is.null(glb_model_metric_smmry)) {
    stats_df <- glb_models_df[, "model_id", FALSE]

    stats_mdl_df <- data.frame()
    for (model_id in stats_df$model_id) {
        stats_mdl_df <- rbind(stats_mdl_df, 
            mypredict_mdl(glb_models_lst[[model_id]], glb_entity_df, glb_rsp_var, 
                          glb_rsp_var_out, model_id, "fit",
                                glb_model_metric_smmry, glb_model_metric, 
                                glb_model_metric_maximize, ret_type="stats"))
    }
    stats_df <- merge(stats_df, stats_mdl_df, all.x=TRUE)
    
    stats_mdl_df <- data.frame()
    for (model_id in stats_df$model_id) {
        stats_mdl_df <- rbind(stats_mdl_df, 
            mypredict_mdl(glb_models_lst[[model_id]], glb_newent_df, glb_rsp_var, 
                          glb_rsp_var_out, model_id, "OOB",
                                glb_model_metric_smmry, glb_model_metric, 
                                glb_model_metric_maximize, ret_type="stats"))
    }
    stats_df <- merge(stats_df, stats_mdl_df, all.x=TRUE)
    
#     tmp_models_df <- orderBy(~model_id, glb_models_df)
#     rownames(tmp_models_df) <- seq(1, nrow(tmp_models_df))
#     all.equal(subset(tmp_models_df[, names(stats_df)], model_id != "Random.myrandom_classfr"),
#               subset(stats_df, model_id != "Random.myrandom_classfr"))
#     print(subset(tmp_models_df[, names(stats_df)], model_id != "Random.myrandom_classfr")[, c("model_id", "max.Accuracy.fit")])
#     print(subset(stats_df, model_id != "Random.myrandom_classfr")[, c("model_id", "max.Accuracy.fit")])

    print("Merging following data into glb_models_df:")
    print(stats_mrg_df <- stats_df[, c(1, grep(glb_model_metric, names(stats_df)))])
    print(tmp_models_df <- orderBy(~model_id, glb_models_df[, c("model_id", grep(glb_model_metric, names(stats_df), value=TRUE))]))

    tmp2_models_df <- glb_models_df[, c("model_id", setdiff(names(glb_models_df), grep(glb_model_metric, names(stats_df), value=TRUE)))]
    tmp3_models_df <- merge(tmp2_models_df, stats_mrg_df, all.x=TRUE, sort=FALSE)
    print(tmp3_models_df)
    print(names(tmp3_models_df))
    print(glb_models_df <- subset(tmp3_models_df, select=-model_id.1))
}
## [1] "in Baseline.Classifier$predict"
## [1] "class(newdata):"
## [1] "matrix"
## [1] "head(newdata):"
##     bucket2008.fctrB2 bucket2008.fctrB3 bucket2008.fctrB4
## 15                  0                 0                 0
## 17                  0                 0                 0
## 48                  0                 0                 0
## 82                  0                 0                 0
## 170                 0                 0                 0
## 199                 0                 0                 0
##     bucket2008.fctrB5      .rnorm
## 15                  0  0.03766206
## 17                  0  1.07112991
## 48                  0 -2.13144213
## 82                  0 -1.08526226
## 170                 0 -0.20923275
## 199                 0 -0.17566037
## [1] "x_names: "
## [1] "bucket2008.fctrB2" "bucket2008.fctrB3" "bucket2008.fctrB4"
## [4] "bucket2008.fctrB5"
## [1] "x_vals: "
## [1] "B1" "B2" "B3" "B4" "B5"
## [1] "length(y):"
## [1] 20000
## [1] "head(y):"
## [1] B1 B1 B1 B1 B1 B1
## Levels: B1 B2 B3 B4 B5
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12003   869   372   158    24
##        B2  1774  1151   489   326    63
##        B3   797   494   276   178    44
##        B4   289   199   165   176    38
##        B5    33    18    22    34     8
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   6.807000e-01   3.150835e-01   6.741879e-01   6.871595e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   2.337804e-03  1.254477e-115 
## [1] "in MFO.Classifier$predict"
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 13426     0     0     0     0
##        B2  3803     0     0     0     0
##        B3  1789     0     0     0     0
##        B4   867     0     0     0     0
##        B5   115     0     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##      0.6713000      0.0000000      0.6647403      0.6778099      0.6713000 
## AccuracyPValue  McnemarPValue 
##      0.5033455            NaN 
##          Prediction
## Reference   B1   B2   B3   B4   B5
##        B1 9031 2579 1182  564   70
##        B2 2516  756  320  194   17
##        B3 1214  347  144   75    9
##        B4  600  146   70   48    3
##        B5   74   23   12    4    2
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##     0.49905000     0.00361021     0.49209605     0.50600422     0.67130000 
## AccuracyPValue  McnemarPValue 
##     1.00000000     0.28881122 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 13426     0     0     0     0
##        B2  3803     0     0     0     0
##        B3  1789     0     0     0     0
##        B4   867     0     0     0     0
##        B5   115     0     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##      0.6713000      0.0000000      0.6647403      0.6778099      0.6713000 
## AccuracyPValue  McnemarPValue 
##      0.5033455            NaN 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12003  1423     0     0     0
##        B2  1774  2029     0     0     0
##        B3   797   992     0     0     0
##        B4   289   578     0     0     0
##        B5    33    82     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.016000e-01   3.390765e-01   6.952047e-01   7.079366e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   1.965498e-20            NaN 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12220  1206     0     0     0
##        B2  1982  1821     0     0     0
##        B3   848   941     0     0     0
##        B4   319   548     0     0     0
##        B5    35    80     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.020500e-01   3.217129e-01   6.956574e-01   7.083838e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   5.406392e-21            NaN 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12537   889     0     0     0
##        B2  2163  1640     0     0     0
##        B3   978   811     0     0     0
##        B4   354   513     0     0     0
##        B5    37    78     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.088500e-01   3.121412e-01   7.024989e-01   7.151403e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   1.753084e-30            NaN 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12664   762     0     0     0
##        B2  2314  1489     0     0     0
##        B3  1017   772     0     0     0
##        B4   373   494     0     0     0
##        B5    38    77     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.076500e-01   2.958182e-01   7.012915e-01   7.139481e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   1.142501e-28            NaN 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12588   654   148    36     0
##        B2  1419  2122   203    59     0
##        B3   767   486   488    48     0
##        B4   336   279    99   153     0
##        B5    41    49    15    10     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.675500e-01   4.861839e-01   7.616324e-01   7.733898e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##  3.187284e-196  1.002543e-280 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12220  1206     0     0     0
##        B2  1982  1821     0     0     0
##        B3   848   941     0     0     0
##        B4   319   548     0     0     0
##        B5    35    80     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.020500e-01   3.217129e-01   6.956574e-01   7.083838e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   5.406392e-21            NaN 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12588   654   148    36     0
##        B2  1419  2122   203    59     0
##        B3   767   486   488    48     0
##        B4   336   279    99   153     0
##        B5    41    49    15    10     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.675500e-01   4.861839e-01   7.616324e-01   7.733898e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##  3.187284e-196  1.002543e-280 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 11972  1166   232    56     0
##        B2  1955  1384   367    98     0
##        B3   889   657   183    60     0
##        B4   346   349   114    57     0
##        B5    39    48    18    10     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   6.798000e-01   2.897201e-01   6.732832e-01   6.862645e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   5.289133e-03  1.795989e-240 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12662   764     0     0     0
##        B2  2322  1482     0     0     0
##        B3   999   790     0     0     0
##        B4   392   474     0     0     0
##        B5    42    73     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.072000e-01   2.942692e-01   7.008387e-01   7.135010e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   5.280171e-28            NaN 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 11972  1166   232    56     0
##        B2  1955  1384   367    98     0
##        B3   889   657   183    60     0
##        B4   346   349   114    57     0
##        B5    39    48    18    10     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   6.798000e-01   2.897201e-01   6.732832e-01   6.862645e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   5.289133e-03  1.795989e-240 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12274  1152     0     0     0
##        B2  1961  1843     0     0     0
##        B3   849   940     0     0     0
##        B4   327   539     0     0     0
##        B5    39    76     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.058500e-01   3.286550e-01   6.994804e-01   7.121597e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   4.639660e-26            NaN 
## [1] "in Baseline.Classifier$predict"
## [1] "class(newdata):"
## [1] "matrix"
## [1] "head(newdata):"
##    bucket2008.fctrB2 bucket2008.fctrB3 bucket2008.fctrB4 bucket2008.fctrB5
## 5                  0                 0                 0                 0
## 25                 0                 0                 0                 0
## 38                 0                 0                 0                 0
## 60                 0                 0                 0                 0
## 69                 0                 0                 0                 0
## 83                 0                 0                 0                 0
##        .rnorm
## 5   0.2563804
## 25  1.2084722
## 38  0.6426727
## 60  0.6402416
## 69 -0.7905369
## 83  0.3301544
## [1] "x_names: "
## [1] "bucket2008.fctrB2" "bucket2008.fctrB3" "bucket2008.fctrB4"
## [4] "bucket2008.fctrB5"
## [1] "x_vals: "
## [1] "B1" "B2" "B3" "B4" "B5"
## [1] "length(y):"
## [1] 20000
## [1] "head(y):"
## [1] B1 B1 B1 B1 B1 B1
## Levels: B1 B2 B3 B4 B5
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12059   840   355   155    17
##        B2  1775  1160   476   337    56
##        B3   782   494   284   188    41
##        B4   296   196   144   189    41
##        B5    34    16    16    36    13
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   6.852500e-01   3.229631e-01   6.787621e-01   6.916841e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   1.294059e-05  4.571070e-127 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12274  1152     0     0     0
##        B2  1961  1843     0     0     0
##        B3   849   940     0     0     0
##        B4   327   539     0     0     0
##        B5    39    76     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.058500e-01   3.286550e-01   6.994804e-01   7.121597e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   4.639660e-26            NaN 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12531   895     0     0     0
##        B2  2199  1605     0     0     0
##        B3   947   842     0     0     0
##        B4   364   502     0     0     0
##        B5    37    78     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.068000e-01   3.069274e-01   7.004362e-01   7.131036e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   2.025337e-27            NaN 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 13426     0     0     0     0
##        B2  3804     0     0     0     0
##        B3  1789     0     0     0     0
##        B4   866     0     0     0     0
##        B5   115     0     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##      0.6713000      0.0000000      0.6647403      0.6778099      0.6713000 
## AccuracyPValue  McnemarPValue 
##      0.5033455            NaN 
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 12059  1367     0     0     0
##        B2  1775  2029     0     0     0
##        B3   782  1007     0     0     0
##        B4   296   570     0     0     0
##        B5    34    81     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   7.044000e-01   3.435108e-01   6.980216e-01   7.107190e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   4.678447e-24            NaN 
## [1] "in MFO.Classifier$predict"
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 13426     0     0     0     0
##        B2  3804     0     0     0     0
##        B3  1789     0     0     0     0
##        B4   866     0     0     0     0
##        B5   115     0     0     0     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##      0.6713000      0.0000000      0.6647403      0.6778099      0.6713000 
## AccuracyPValue  McnemarPValue 
##      0.5033455            NaN 
##          Prediction
## Reference   B1   B2   B3   B4   B5
##        B1 9045 2504 1193  604   80
##        B2 2563  710  339  169   23
##        B3 1186  346  177   67   13
##        B4  578  158   84   42    4
##        B5   78   21    9    7    0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##     0.49870000     0.00332866     0.49174612     0.50565426     0.67130000 
## AccuracyPValue  McnemarPValue 
##     1.00000000     0.87050089 
## [1] "Merging following data into glb_models_df:"
##                       model_id min.loss.error.fit min.loss.error.OOB
## 1  All.X.lser.no.cp.4015.rpart            0.61685            0.77965
## 2   All.X.lser.no.cp.opt.rpart            0.79910            0.80030
## 3  All.X.lser.ys.cp.4015.rpart            0.61685            0.77965
## 4   All.X.lser.ys.cp.opt.rpart            0.76550            0.76180
## 5    Baseline.mybaseln_classfr            0.74645            0.73650
## 6    Interact.High.cor.y.rpart            0.76550            0.76180
## 7              Low.cor.X.rpart            0.78445            0.78605
## 8         Max.cor.Y.cv.0.rpart            1.04420            1.04400
## 9         Max.cor.Y.cv.G.rpart            0.74725            0.74365
## 10           MFO.myMFO_classfr            1.04420            1.04400
## 11     Random.myrandom_classfr            1.17310            1.17475
##                       model_id min.loss.error.fit min.loss.error.OOB
## 9  All.X.lser.no.cp.4015.rpart                 NA                 NA
## 8   All.X.lser.no.cp.opt.rpart                 NA                 NA
## 11 All.X.lser.ys.cp.4015.rpart          0.7723494            0.77965
## 10  All.X.lser.ys.cp.opt.rpart          0.7768504            0.76180
## 1    Baseline.mybaseln_classfr                 NA                 NA
## 6    Interact.High.cor.y.rpart                 NA                 NA
## 7              Low.cor.X.rpart                 NA                 NA
## 4         Max.cor.Y.cv.0.rpart                 NA                 NA
## 5         Max.cor.Y.cv.G.rpart                 NA                 NA
## 2            MFO.myMFO_classfr                 NA                 NA
## 3      Random.myrandom_classfr                 NA                 NA
##                       model_id                  model_id.1
## 1    Baseline.mybaseln_classfr   Baseline.mybaseln_classfr
## 2            MFO.myMFO_classfr           MFO.myMFO_classfr
## 3      Random.myrandom_classfr     Random.myrandom_classfr
## 4         Max.cor.Y.cv.0.rpart        Max.cor.Y.cv.0.rpart
## 5         Max.cor.Y.cv.G.rpart        Max.cor.Y.cv.G.rpart
## 6    Interact.High.cor.y.rpart   Interact.High.cor.y.rpart
## 7              Low.cor.X.rpart             Low.cor.X.rpart
## 8   All.X.lser.no.cp.opt.rpart  All.X.lser.no.cp.opt.rpart
## 9  All.X.lser.no.cp.4015.rpart All.X.lser.no.cp.4015.rpart
## 10  All.X.lser.ys.cp.opt.rpart  All.X.lser.ys.cp.opt.rpart
## 11 All.X.lser.ys.cp.4015.rpart All.X.lser.ys.cp.4015.rpart
##        model_method
## 1  mybaseln_classfr
## 2     myMFO_classfr
## 3  myrandom_classfr
## 4             rpart
## 5             rpart
## 6             rpart
## 7             rpart
## 8             rpart
## 9             rpart
## 10            rpart
## 11            rpart
##                                                                                                                                              feats
## 1                                                                                                                          bucket2008.fctr, .rnorm
## 2                                                                                                                                           .rnorm
## 3                                                                                                                                           .rnorm
## 4                                                                                                                                       bucket2008
## 5                                                                                                                                       bucket2008
## 6                                                                                                                    bucket2008, reimbursement2008
## 7                     bucket2008, diabetes, ihd, kidney, heart.failure, copd, depression, alzheimers, arthritis, osteoporosis, cancer, stroke, age
## 8  age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
## 9  age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
## 10 age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
## 11 age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
##    max.nTuningRuns min.elapsedtime.everything min.elapsedtime.final
## 1                0                      0.425                 0.003
## 2                0                      0.258                 0.005
## 3                0                      0.231                 0.003
## 4                0                      0.779                 0.248
## 5                3                      2.316                 0.246
## 6                3                      2.997                 0.361
## 7                3                      6.536                 0.866
## 8                3                      6.806                 0.919
## 9                1                      5.426                 0.914
## 10               3                      7.386                 0.917
## 11               1                      5.857                 0.916
##    max.Accuracy.fit max.AccuracyLower.fit max.AccuracyUpper.fit
## 1         0.6807000             0.6741879             0.6871595
## 2         0.6713000             0.6647403             0.6778099
## 3         0.4978000             0.4908463             0.5047543
## 4         0.6713000             0.6647403             0.6778099
## 5         0.7015991             0.6952047             0.7079366
## 6         0.6964492             0.6956574             0.7083838
## 7         0.7092992             0.7024989             0.7151403
## 8         0.7074489             0.7012915             0.7139481
## 9         0.6782992             0.7616324             0.7733898
## 10        0.7020500             0.6956574             0.7083838
## 11        0.7675500             0.7616324             0.7733898
##    max.Kappa.fit max.Accuracy.OOB max.AccuracyLower.OOB
## 1   3.150835e-01          0.68525             0.6787621
## 2   0.000000e+00          0.67130             0.6647403
## 3  -7.473179e-05          0.49900             0.4920461
## 4   0.000000e+00          0.67130             0.6647403
## 5   3.390926e-01          0.70440             0.6980216
## 6   3.134828e-01          0.70585             0.6994804
## 7   3.218867e-01          0.70680             0.7004362
## 8   3.038255e-01          0.70720             0.7008387
## 9   2.927210e-01          0.67980             0.6732832
## 10  3.217129e-01          0.70585             0.6994804
## 11  4.861839e-01          0.67980             0.6732832
##    max.AccuracyUpper.OOB max.Kappa.OOB min.SSE.fit max.AccuracySD.fit
## 1              0.6916841   0.322963052           0                 NA
## 2              0.6778099   0.000000000           0                 NA
## 3              0.5059542   0.003477783           0                 NA
## 4              0.6778099   0.000000000           0                 NA
## 5              0.7107190   0.343510796           0        0.004432663
## 6              0.7121597   0.328654953           0        0.004645926
## 7              0.7131036   0.306927409           0        0.005333283
## 8              0.7135010   0.294269180           0        0.006818137
## 9              0.6862645   0.289720052           0        0.006853054
## 10             0.7121597   0.328654953           0                 NA
## 11             0.6862645   0.289720052           0                 NA
##    max.KappaSD.fit min.loss.errorSD.fit min.loss.error.fit
## 1               NA                   NA            0.74645
## 2               NA                   NA            1.04420
## 3               NA                   NA            1.17310
## 4               NA                   NA            1.04420
## 5      0.007882575                   NA            0.74725
## 6      0.013637821                   NA            0.76550
## 7      0.012387416                   NA            0.78445
## 8      0.020611981                   NA            0.79910
## 9      0.014553753                   NA            0.61685
## 10              NA           0.01485311            0.76550
## 11              NA           0.01641269            0.61685
##    min.loss.error.OOB
## 1             0.73650
## 2             1.04400
## 3             1.17475
## 4             1.04400
## 5             0.74365
## 6             0.76180
## 7             0.78605
## 8             0.80030
## 9             0.77965
## 10            0.76180
## 11            0.77965
##  [1] "model_id"                   "model_id.1"                
##  [3] "model_method"               "feats"                     
##  [5] "max.nTuningRuns"            "min.elapsedtime.everything"
##  [7] "min.elapsedtime.final"      "max.Accuracy.fit"          
##  [9] "max.AccuracyLower.fit"      "max.AccuracyUpper.fit"     
## [11] "max.Kappa.fit"              "max.Accuracy.OOB"          
## [13] "max.AccuracyLower.OOB"      "max.AccuracyUpper.OOB"     
## [15] "max.Kappa.OOB"              "min.SSE.fit"               
## [17] "max.AccuracySD.fit"         "max.KappaSD.fit"           
## [19] "min.loss.errorSD.fit"       "min.loss.error.fit"        
## [21] "min.loss.error.OOB"        
##                       model_id     model_method
## 1    Baseline.mybaseln_classfr mybaseln_classfr
## 2            MFO.myMFO_classfr    myMFO_classfr
## 3      Random.myrandom_classfr myrandom_classfr
## 4         Max.cor.Y.cv.0.rpart            rpart
## 5         Max.cor.Y.cv.G.rpart            rpart
## 6    Interact.High.cor.y.rpart            rpart
## 7              Low.cor.X.rpart            rpart
## 8   All.X.lser.no.cp.opt.rpart            rpart
## 9  All.X.lser.no.cp.4015.rpart            rpart
## 10  All.X.lser.ys.cp.opt.rpart            rpart
## 11 All.X.lser.ys.cp.4015.rpart            rpart
##                                                                                                                                              feats
## 1                                                                                                                          bucket2008.fctr, .rnorm
## 2                                                                                                                                           .rnorm
## 3                                                                                                                                           .rnorm
## 4                                                                                                                                       bucket2008
## 5                                                                                                                                       bucket2008
## 6                                                                                                                    bucket2008, reimbursement2008
## 7                     bucket2008, diabetes, ihd, kidney, heart.failure, copd, depression, alzheimers, arthritis, osteoporosis, cancer, stroke, age
## 8  age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
## 9  age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
## 10 age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
## 11 age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
##    max.nTuningRuns min.elapsedtime.everything min.elapsedtime.final
## 1                0                      0.425                 0.003
## 2                0                      0.258                 0.005
## 3                0                      0.231                 0.003
## 4                0                      0.779                 0.248
## 5                3                      2.316                 0.246
## 6                3                      2.997                 0.361
## 7                3                      6.536                 0.866
## 8                3                      6.806                 0.919
## 9                1                      5.426                 0.914
## 10               3                      7.386                 0.917
## 11               1                      5.857                 0.916
##    max.Accuracy.fit max.AccuracyLower.fit max.AccuracyUpper.fit
## 1         0.6807000             0.6741879             0.6871595
## 2         0.6713000             0.6647403             0.6778099
## 3         0.4978000             0.4908463             0.5047543
## 4         0.6713000             0.6647403             0.6778099
## 5         0.7015991             0.6952047             0.7079366
## 6         0.6964492             0.6956574             0.7083838
## 7         0.7092992             0.7024989             0.7151403
## 8         0.7074489             0.7012915             0.7139481
## 9         0.6782992             0.7616324             0.7733898
## 10        0.7020500             0.6956574             0.7083838
## 11        0.7675500             0.7616324             0.7733898
##    max.Kappa.fit max.Accuracy.OOB max.AccuracyLower.OOB
## 1   3.150835e-01          0.68525             0.6787621
## 2   0.000000e+00          0.67130             0.6647403
## 3  -7.473179e-05          0.49900             0.4920461
## 4   0.000000e+00          0.67130             0.6647403
## 5   3.390926e-01          0.70440             0.6980216
## 6   3.134828e-01          0.70585             0.6994804
## 7   3.218867e-01          0.70680             0.7004362
## 8   3.038255e-01          0.70720             0.7008387
## 9   2.927210e-01          0.67980             0.6732832
## 10  3.217129e-01          0.70585             0.6994804
## 11  4.861839e-01          0.67980             0.6732832
##    max.AccuracyUpper.OOB max.Kappa.OOB min.SSE.fit max.AccuracySD.fit
## 1              0.6916841   0.322963052           0                 NA
## 2              0.6778099   0.000000000           0                 NA
## 3              0.5059542   0.003477783           0                 NA
## 4              0.6778099   0.000000000           0                 NA
## 5              0.7107190   0.343510796           0        0.004432663
## 6              0.7121597   0.328654953           0        0.004645926
## 7              0.7131036   0.306927409           0        0.005333283
## 8              0.7135010   0.294269180           0        0.006818137
## 9              0.6862645   0.289720052           0        0.006853054
## 10             0.7121597   0.328654953           0                 NA
## 11             0.6862645   0.289720052           0                 NA
##    max.KappaSD.fit min.loss.errorSD.fit min.loss.error.fit
## 1               NA                   NA            0.74645
## 2               NA                   NA            1.04420
## 3               NA                   NA            1.17310
## 4               NA                   NA            1.04420
## 5      0.007882575                   NA            0.74725
## 6      0.013637821                   NA            0.76550
## 7      0.012387416                   NA            0.78445
## 8      0.020611981                   NA            0.79910
## 9      0.014553753                   NA            0.61685
## 10              NA           0.01485311            0.76550
## 11              NA           0.01641269            0.61685
##    min.loss.error.OOB
## 1             0.73650
## 2             1.04400
## 3             1.17475
## 4             1.04400
## 5             0.74365
## 6             0.76180
## 7             0.78605
## 8             0.80030
## 9             0.77965
## 10            0.76180
## 11            0.77965
plt_models_df <- glb_models_df[, -grep("SD|Upper|Lower", names(glb_models_df))]
for (var in grep("^min.", names(plt_models_df), value=TRUE)) {
    plt_models_df[, sub("min.", "inv.", var)] <- 
        #ifelse(all(is.na(tmp <- plt_models_df[, var])), NA, 1.0 / tmp)
        1.0 / plt_models_df[, var]
    plt_models_df <- plt_models_df[ , -grep(var, names(plt_models_df))]
}
print(plt_models_df)
##                       model_id     model_method
## 1    Baseline.mybaseln_classfr mybaseln_classfr
## 2            MFO.myMFO_classfr    myMFO_classfr
## 3      Random.myrandom_classfr myrandom_classfr
## 4         Max.cor.Y.cv.0.rpart            rpart
## 5         Max.cor.Y.cv.G.rpart            rpart
## 6    Interact.High.cor.y.rpart            rpart
## 7              Low.cor.X.rpart            rpart
## 8   All.X.lser.no.cp.opt.rpart            rpart
## 9  All.X.lser.no.cp.4015.rpart            rpart
## 10  All.X.lser.ys.cp.opt.rpart            rpart
## 11 All.X.lser.ys.cp.4015.rpart            rpart
##                                                                                                                                              feats
## 1                                                                                                                          bucket2008.fctr, .rnorm
## 2                                                                                                                                           .rnorm
## 3                                                                                                                                           .rnorm
## 4                                                                                                                                       bucket2008
## 5                                                                                                                                       bucket2008
## 6                                                                                                                    bucket2008, reimbursement2008
## 7                     bucket2008, diabetes, ihd, kidney, heart.failure, copd, depression, alzheimers, arthritis, osteoporosis, cancer, stroke, age
## 8  age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
## 9  age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
## 10 age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
## 11 age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
##    max.nTuningRuns max.Accuracy.fit max.Kappa.fit max.Accuracy.OOB
## 1                0        0.6807000  3.150835e-01          0.68525
## 2                0        0.6713000  0.000000e+00          0.67130
## 3                0        0.4978000 -7.473179e-05          0.49900
## 4                0        0.6713000  0.000000e+00          0.67130
## 5                3        0.7015991  3.390926e-01          0.70440
## 6                3        0.6964492  3.134828e-01          0.70585
## 7                3        0.7092992  3.218867e-01          0.70680
## 8                3        0.7074489  3.038255e-01          0.70720
## 9                1        0.6782992  2.927210e-01          0.67980
## 10               3        0.7020500  3.217129e-01          0.70585
## 11               1        0.7675500  4.861839e-01          0.67980
##    max.Kappa.OOB inv.elapsedtime.everything inv.elapsedtime.final
## 1    0.322963052                  2.3529412            333.333333
## 2    0.000000000                  3.8759690            200.000000
## 3    0.003477783                  4.3290043            333.333333
## 4    0.000000000                  1.2836970              4.032258
## 5    0.343510796                  0.4317789              4.065041
## 6    0.328654953                  0.3336670              2.770083
## 7    0.306927409                  0.1529988              1.154734
## 8    0.294269180                  0.1469292              1.088139
## 9    0.289720052                  0.1842978              1.094092
## 10   0.328654953                  0.1353913              1.090513
## 11   0.289720052                  0.1707359              1.091703
##    inv.SSE.fit inv.loss.error.fit inv.loss.error.OOB
## 1          Inf          1.3396745          1.3577733
## 2          Inf          0.9576709          0.9578544
## 3          Inf          0.8524422          0.8512449
## 4          Inf          0.9576709          0.9578544
## 5          Inf          1.3382402          1.3447186
## 6          Inf          1.3063357          1.3126805
## 7          Inf          1.2747785          1.2721837
## 8          Inf          1.2514078          1.2495314
## 9          Inf          1.6211397          1.2826268
## 10         Inf          1.3063357          1.3126805
## 11         Inf          1.6211397          1.2826268
print(myplot_radar(radar_inp_df=plt_models_df))
## Warning in myplot_radar(radar_inp_df = plt_models_df): Not plotting
## columns with all Infs: inv.SSE.fit
## Warning in RColorBrewer::brewer.pal(n, pal): n too large, allowed maximum for palette Set1 is 9
## Returning the palette you asked for with that many colors
## Warning: The shape palette can deal with a maximum of 6 discrete values
## because more than 6 becomes difficult to discriminate; you have
## 11. Consider specifying shapes manually. if you must have them.
## Warning: Removed 50 rows containing missing values (geom_point).
## Warning in RColorBrewer::brewer.pal(n, pal): n too large, allowed maximum for palette Set1 is 9
## Returning the palette you asked for with that many colors
## Warning: The shape palette can deal with a maximum of 6 discrete values
## because more than 6 becomes difficult to discriminate; you have
## 11. Consider specifying shapes manually. if you must have them.

print(myplot_radar(radar_inp_df=subset(plt_models_df, 
        !(model_id %in% grep("random|MFO", plt_models_df$model_id, value=TRUE)))))
## Warning in myplot_radar(radar_inp_df = subset(plt_models_df, !(model_id
## %in% : Not plotting columns with all Infs: inv.SSE.fit
## Warning: The shape palette can deal with a maximum of 6 discrete values
## because more than 6 becomes difficult to discriminate; you have 9.
## Consider specifying shapes manually. if you must have them.
## Warning: Removed 30 rows containing missing values (geom_point).
## Warning: The shape palette can deal with a maximum of 6 discrete values
## because more than 6 becomes difficult to discriminate; you have 9.
## Consider specifying shapes manually. if you must have them.

# Compute CI for <metric>SD
glb_models_df <- mutate(glb_models_df, 
                max.df = ifelse(max.nTuningRuns > 1, max.nTuningRuns - 1, NA),
                min.sd2ci.scaler = ifelse(is.na(max.df), NA, qt(0.975, max.df)))
for (var in grep("SD", names(glb_models_df), value=TRUE)) {
    # Does CI alredy exist ?
    var_components <- unlist(strsplit(var, "SD"))
    varActul <- paste0(var_components[1],          var_components[2])
    varUpper <- paste0(var_components[1], "Upper", var_components[2])
    varLower <- paste0(var_components[1], "Lower", var_components[2])
    if (varUpper %in% names(glb_models_df)) {
        warning(varUpper, " already exists in glb_models_df")
        # Assuming Lower also exists
        next
    }    
    print(sprintf("var:%s", var))
    # CI is dependent on sample size in t distribution; df=n-1
    glb_models_df[, varUpper] <- glb_models_df[, varActul] + 
        glb_models_df[, "min.sd2ci.scaler"] * glb_models_df[, var]
    glb_models_df[, varLower] <- glb_models_df[, varActul] - 
        glb_models_df[, "min.sd2ci.scaler"] * glb_models_df[, var]
}
## Warning: max.AccuracyUpper.fit already exists in glb_models_df
## [1] "var:max.KappaSD.fit"
## [1] "var:min.loss.errorSD.fit"
# Plot metrics with CI
plt_models_df <- glb_models_df[, "model_id", FALSE]
pltCI_models_df <- glb_models_df[, "model_id", FALSE]
for (var in grep("Upper", names(glb_models_df), value=TRUE)) {
    var_components <- unlist(strsplit(var, "Upper"))
    col_name <- unlist(paste(var_components, collapse=""))
    plt_models_df[, col_name] <- glb_models_df[, col_name]
    for (name in paste0(var_components[1], c("Upper", "Lower"), var_components[2]))
        pltCI_models_df[, name] <- glb_models_df[, name]
}

build_statsCI_data <- function(plt_models_df) {
    mltd_models_df <- melt(plt_models_df, id.vars="model_id")
    mltd_models_df$data <- sapply(1:nrow(mltd_models_df), 
        function(row_ix) tail(unlist(strsplit(as.character(
            mltd_models_df[row_ix, "variable"]), "[.]")), 1))
    mltd_models_df$label <- sapply(1:nrow(mltd_models_df), 
        function(row_ix) head(unlist(strsplit(as.character(
            mltd_models_df[row_ix, "variable"]), paste0(".", mltd_models_df[row_ix, "data"]))), 1))
    #print(mltd_models_df)
    
    return(mltd_models_df)
}
mltd_models_df <- build_statsCI_data(plt_models_df)

mltdCI_models_df <- melt(pltCI_models_df, id.vars="model_id")
for (row_ix in 1:nrow(mltdCI_models_df)) {
    for (type in c("Upper", "Lower")) {
        if (length(var_components <- unlist(strsplit(
                as.character(mltdCI_models_df[row_ix, "variable"]), type))) > 1) {
            #print(sprintf("row_ix:%d; type:%s; ", row_ix, type))
            mltdCI_models_df[row_ix, "label"] <- var_components[1]
            mltdCI_models_df[row_ix, "data"] <- unlist(strsplit(var_components[2], "[.]"))[2]
            mltdCI_models_df[row_ix, "type"] <- type
            break
        }
    }    
}
#print(mltdCI_models_df)
# castCI_models_df <- dcast(mltdCI_models_df, value ~ type, fun.aggregate=sum)
# print(castCI_models_df)
wideCI_models_df <- reshape(subset(mltdCI_models_df, select=-variable), 
                            timevar="type", 
        idvar=setdiff(names(mltdCI_models_df), c("type", "value", "variable")), 
                            direction="wide")
#print(wideCI_models_df)
mrgdCI_models_df <- merge(wideCI_models_df, mltd_models_df, all.x=TRUE)
#print(mrgdCI_models_df)

# Merge stats back in if CIs don't exist
goback_vars <- c()
for (var in unique(mltd_models_df$label)) {
    for (type in unique(mltd_models_df$data)) {
        var_type <- paste0(var, ".", type)
        # if this data is already present, next
        if (var_type %in% unique(paste(mltd_models_df$label, mltd_models_df$data, sep=".")))
            next
        #print(sprintf("var_type:%s", var_type))
        goback_vars <- c(goback_vars, var_type)
    }
}

mltd_goback_df <- build_statsCI_data(glb_models_df[, c("model_id", goback_vars)])
mltd_models_df <- rbind(mltd_models_df, mltd_goback_df)

mltd_models_df <- merge(mltd_models_df, glb_models_df[, c("model_id", "model_method")], all.x=TRUE)

# print(myplot_bar(mltd_models_df, "model_id", "value", colorcol_name="data") + 
#         geom_errorbar(data=mrgdCI_models_df, 
#             mapping=aes(x=model_id, ymax=value.Upper, ymin=value.Lower), width=0.5) + 
#           facet_grid(label ~ data, scales="free") + 
#           theme(axis.text.x = element_text(angle = 45,vjust = 1)))
# mltd_models_df <- orderBy(~ value +variable +data +label + model_method + model_id, 
#                           mltd_models_df)
print(myplot_bar(mltd_models_df, "model_id", "value", colorcol_name="model_method") + 
        geom_errorbar(data=mrgdCI_models_df, 
            mapping=aes(x=model_id, ymax=value.Upper, ymin=value.Lower), width=0.5) + 
          facet_grid(label ~ data, scales="free") + 
          theme(axis.text.x = element_text(angle = 90,vjust = 0.5)))
## Warning: Stacking not well defined when ymin != 0

if (glb_is_regression) {
    print(orderBy(~ -R.sq.OOB -Adj.R.sq.fit, glb_models_df))
    stop("glb_sel_mdl not selected")
    print(myplot_scatter(plot_models_df, "Adj.R.sq.fit", "R.sq.OOB") + 
          geom_text(aes(label=feats.label), data=plot_models_df, color="NavyBlue", 
                    size=3.5, angle=45))
}    

if (glb_is_classification) {
    print(tmp_models_df <- orderBy(glb_model_sel_frmla, glb_models_df))    
    print("Metrics used for model selection:"); print(glb_model_sel_frmla)
    print(sprintf("Best model id: %s", tmp_models_df[1, "model_id"]))
    
    if (is.null(glb_sel_mdl_id)) 
        { glb_sel_mdl_id <- tmp_models_df[1, "model_id"] } else 
        print(sprintf("User specified selection: %s", glb_sel_mdl_id))   
    
    myprint_mdl(glb_sel_mdl <- glb_models_lst[[glb_sel_mdl_id]])
}        
##                       model_id     model_method
## 1    Baseline.mybaseln_classfr mybaseln_classfr
## 5         Max.cor.Y.cv.G.rpart            rpart
## 6    Interact.High.cor.y.rpart            rpart
## 10  All.X.lser.ys.cp.opt.rpart            rpart
## 9  All.X.lser.no.cp.4015.rpart            rpart
## 11 All.X.lser.ys.cp.4015.rpart            rpart
## 7              Low.cor.X.rpart            rpart
## 8   All.X.lser.no.cp.opt.rpart            rpart
## 2            MFO.myMFO_classfr    myMFO_classfr
## 4         Max.cor.Y.cv.0.rpart            rpart
## 3      Random.myrandom_classfr myrandom_classfr
##                                                                                                                                              feats
## 1                                                                                                                          bucket2008.fctr, .rnorm
## 5                                                                                                                                       bucket2008
## 6                                                                                                                    bucket2008, reimbursement2008
## 10 age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
## 9  age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
## 11 age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
## 7                     bucket2008, diabetes, ihd, kidney, heart.failure, copd, depression, alzheimers, arthritis, osteoporosis, cancer, stroke, age
## 8  age, alzheimers, arthritis, cancer, copd, depression, diabetes, heart.failure, ihd, kidney, osteoporosis, stroke, reimbursement2008, bucket2008
## 2                                                                                                                                           .rnorm
## 4                                                                                                                                       bucket2008
## 3                                                                                                                                           .rnorm
##    max.nTuningRuns min.elapsedtime.everything min.elapsedtime.final
## 1                0                      0.425                 0.003
## 5                3                      2.316                 0.246
## 6                3                      2.997                 0.361
## 10               3                      7.386                 0.917
## 9                1                      5.426                 0.914
## 11               1                      5.857                 0.916
## 7                3                      6.536                 0.866
## 8                3                      6.806                 0.919
## 2                0                      0.258                 0.005
## 4                0                      0.779                 0.248
## 3                0                      0.231                 0.003
##    max.Accuracy.fit max.AccuracyLower.fit max.AccuracyUpper.fit
## 1         0.6807000             0.6741879             0.6871595
## 5         0.7015991             0.6952047             0.7079366
## 6         0.6964492             0.6956574             0.7083838
## 10        0.7020500             0.6956574             0.7083838
## 9         0.6782992             0.7616324             0.7733898
## 11        0.7675500             0.7616324             0.7733898
## 7         0.7092992             0.7024989             0.7151403
## 8         0.7074489             0.7012915             0.7139481
## 2         0.6713000             0.6647403             0.6778099
## 4         0.6713000             0.6647403             0.6778099
## 3         0.4978000             0.4908463             0.5047543
##    max.Kappa.fit max.Accuracy.OOB max.AccuracyLower.OOB
## 1   3.150835e-01          0.68525             0.6787621
## 5   3.390926e-01          0.70440             0.6980216
## 6   3.134828e-01          0.70585             0.6994804
## 10  3.217129e-01          0.70585             0.6994804
## 9   2.927210e-01          0.67980             0.6732832
## 11  4.861839e-01          0.67980             0.6732832
## 7   3.218867e-01          0.70680             0.7004362
## 8   3.038255e-01          0.70720             0.7008387
## 2   0.000000e+00          0.67130             0.6647403
## 4   0.000000e+00          0.67130             0.6647403
## 3  -7.473179e-05          0.49900             0.4920461
##    max.AccuracyUpper.OOB max.Kappa.OOB min.SSE.fit max.AccuracySD.fit
## 1              0.6916841   0.322963052           0                 NA
## 5              0.7107190   0.343510796           0        0.004432663
## 6              0.7121597   0.328654953           0        0.004645926
## 10             0.7121597   0.328654953           0                 NA
## 9              0.6862645   0.289720052           0        0.006853054
## 11             0.6862645   0.289720052           0                 NA
## 7              0.7131036   0.306927409           0        0.005333283
## 8              0.7135010   0.294269180           0        0.006818137
## 2              0.6778099   0.000000000           0                 NA
## 4              0.6778099   0.000000000           0                 NA
## 3              0.5059542   0.003477783           0                 NA
##    max.KappaSD.fit min.loss.errorSD.fit min.loss.error.fit
## 1               NA                   NA            0.74645
## 5      0.007882575                   NA            0.74725
## 6      0.013637821                   NA            0.76550
## 10              NA           0.01485311            0.76550
## 9      0.014553753                   NA            0.61685
## 11              NA           0.01641269            0.61685
## 7      0.012387416                   NA            0.78445
## 8      0.020611981                   NA            0.79910
## 2               NA                   NA            1.04420
## 4               NA                   NA            1.04420
## 3               NA                   NA            1.17310
##    min.loss.error.OOB max.df min.sd2ci.scaler max.KappaUpper.fit
## 1             0.73650     NA               NA                 NA
## 5             0.74365      2         4.302653          0.3730086
## 6             0.76180      2         4.302653          0.3721616
## 10            0.76180      2         4.302653                 NA
## 9             0.77965     NA               NA                 NA
## 11            0.77965     NA               NA                 NA
## 7             0.78605      2         4.302653          0.3751855
## 8             0.80030      2         4.302653          0.3925117
## 2             1.04400     NA               NA                 NA
## 4             1.04400     NA               NA                 NA
## 3             1.17475     NA               NA                 NA
##    max.KappaLower.fit min.loss.errorUpper.fit min.loss.errorLower.fit
## 1                  NA                      NA                      NA
## 5           0.3051766                      NA                      NA
## 6           0.2548040                      NA                      NA
## 10                 NA               0.8294078               0.7015922
## 9                  NA                      NA                      NA
## 11                 NA                      NA                      NA
## 7           0.2685880                      NA                      NA
## 8           0.2151393                      NA                      NA
## 2                  NA                      NA                      NA
## 4                  NA                      NA                      NA
## 3                  NA                      NA                      NA
## [1] "Metrics used for model selection:"
## ~+min.loss.error.OOB - max.Accuracy.OOB - max.Kappa.OOB
## [1] "Best model id: Baseline.mybaseln_classfr"
## [1] "User specified selection: All.X.lser.ys.cp.4015.rpart"
## Warning: labs do not fit even at cex 0.15, there may be some overplotting

## Call:
## rpart(formula = .outcome ~ ., control = list(minsplit = 20, minbucket = 7, 
##     cp = 0, maxcompete = 4, maxsurrogate = 5, usesurrogate = 2, 
##     surrogatestyle = 0, maxdepth = 30, xval = 0))
##   n= 20000 
## 
##              CP nsplit rel error
## 1  4.677517e-02      0 1.0000000
## 2  1.703681e-02      2 0.9064497
## 3  5.019775e-03      3 0.8894128
## 4  3.346517e-03      4 0.8843931
## 5  2.053544e-03      7 0.8743535
## 6  1.216915e-03      9 0.8702464
## 7  1.064801e-03     11 0.8678126
## 8  9.126863e-04     16 0.8624886
## 9  8.746577e-04     17 0.8615759
## 10 8.619815e-04     26 0.8522969
## 11 7.605720e-04     29 0.8497110
## 12 6.084576e-04     34 0.8459081
## 13 5.324004e-04     44 0.8398235
## 14 5.070480e-04     50 0.8366291
## 15 4.563432e-04     83 0.8183754
## 16 4.056384e-04    110 0.8060542
## 17 3.802860e-04    115 0.8039246
## 18 3.650745e-04    134 0.7966231
## 19 3.549336e-04    144 0.7928202
## 20 3.422574e-04    164 0.7852145
## 21 3.295812e-04    168 0.7838455
## 22 3.042288e-04    174 0.7818680
## 23 2.788764e-04    222 0.7671129
## 24 2.738059e-04    230 0.7648312
## 25 2.662002e-04    238 0.7620931
## 26 2.535240e-04    246 0.7599635
## 27 2.281716e-04    262 0.7555522
## 28 2.028192e-04    301 0.7449042
## 29 1.901430e-04    329 0.7380590
## 30 1.521144e-04    345 0.7345604
## 31 1.303838e-04    438 0.7191968
## 32 1.216915e-04    445 0.7182841
## 33 1.014096e-04    459 0.7161545
## 34 8.450799e-05    475 0.7143292
## 35 7.605720e-05    485 0.7134165
## 36 6.519188e-05    527 0.7102221
## 37 6.084576e-05    560 0.7079404
## 38 5.070480e-05    567 0.7074840
## 39 5.000000e-05    573 0.7071798
## 
## Variable importance
## reimbursement2008        bucket2008          diabetes               ihd 
##                32                17                12                12 
##     heart.failure            kidney               age        depression 
##                10                 8                 4                 1 
##      osteoporosis              copd         arthritis        alzheimers 
##                 1                 1                 1                 1 
## 
## Node number 1: 20000 observations,    complexity param=0.04677517
##   predicted class=B1  expected loss=0.3287  P(node) =1
##     class counts: 13426  3803  1789   867   115
##    probabilities: 0.671 0.190 0.089 0.043 0.006 
##   left son=2 (12142 obs) right son=3 (7858 obs)
##   Primary splits:
##       reimbursement2008 < 1565   to the left,  improve=1764.3490, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=1460.0660, (0 missing)
##       ihd               < 0.5    to the left,  improve=1206.8110, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1184.0260, (0 missing)
##       heart.failure     < 0.5    to the left,  improve= 934.8263, (0 missing)
##   Surrogate splits:
##       bucket2008    < 1.5    to the left,  agree=0.862, adj=0.650, (0 split)
##       ihd           < 0.5    to the left,  agree=0.790, adj=0.466, (0 split)
##       diabetes      < 0.5    to the left,  agree=0.784, adj=0.449, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.763, adj=0.397, (0 split)
##       kidney        < 0.5    to the left,  agree=0.732, adj=0.319, (0 split)
## 
## Node number 2: 12142 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.1275737  P(node) =0.6071
##     class counts: 10593   933   433   164    19
##    probabilities: 0.872 0.077 0.036 0.014 0.002 
##   left son=4 (6456 obs) right son=5 (5686 obs)
##   Primary splits:
##       reimbursement2008 < 195    to the left,  improve=186.28990, (0 missing)
##       diabetes          < 0.5    to the left,  improve=101.76450, (0 missing)
##       ihd               < 0.5    to the left,  improve= 95.31422, (0 missing)
##       heart.failure     < 0.5    to the left,  improve= 56.11198, (0 missing)
##       depression        < 0.5    to the left,  improve= 42.49380, (0 missing)
##   Surrogate splits:
##       ihd           < 0.5    to the left,  agree=0.707, adj=0.374, (0 split)
##       diabetes      < 0.5    to the left,  agree=0.692, adj=0.343, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.630, adj=0.209, (0 split)
##       depression    < 0.5    to the left,  agree=0.608, adj=0.163, (0 split)
##       osteoporosis  < 0.5    to the left,  agree=0.606, adj=0.158, (0 split)
## 
## Node number 3: 7858 observations,    complexity param=0.04677517
##   predicted class=B2  expected loss=0.6347671  P(node) =0.3929
##     class counts:  2833  2870  1356   703    96
##    probabilities: 0.361 0.365 0.173 0.089 0.012 
##   left son=6 (3262 obs) right son=7 (4596 obs)
##   Primary splits:
##       reimbursement2008 < 3425   to the left,  improve=138.79980, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=127.82570, (0 missing)
##       kidney            < 0.5    to the left,  improve=108.01160, (0 missing)
##       diabetes          < 0.5    to the left,  improve= 91.30944, (0 missing)
##       ihd               < 0.5    to the left,  improve= 83.33736, (0 missing)
##   Surrogate splits:
##       bucket2008    < 1.5    to the left,  agree=0.935, adj=0.844, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.636, adj=0.122, (0 split)
##       kidney        < 0.5    to the left,  agree=0.634, adj=0.117, (0 split)
##       ihd           < 0.5    to the left,  agree=0.631, adj=0.111, (0 split)
##       diabetes      < 0.5    to the left,  agree=0.623, adj=0.092, (0 split)
## 
## Node number 4: 6456 observations
##   predicted class=B1  expected loss=0.03175341  P(node) =0.3228
##     class counts:  6251   108    69    25     3
##    probabilities: 0.968 0.017 0.011 0.004 0.000 
## 
## Node number 5: 5686 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.23637  P(node) =0.2843
##     class counts:  4342   825   364   139    16
##    probabilities: 0.764 0.145 0.064 0.024 0.003 
##   left son=10 (2374 obs) right son=11 (3312 obs)
##   Primary splits:
##       reimbursement2008 < 685    to the left,  improve=27.349520, (0 missing)
##       diabetes          < 0.5    to the left,  improve=17.262440, (0 missing)
##       ihd               < 0.5    to the left,  improve=13.874990, (0 missing)
##       heart.failure     < 0.5    to the left,  improve= 8.237337, (0 missing)
##       depression        < 0.5    to the left,  improve= 7.708074, (0 missing)
##   Surrogate splits:
##       diabetes < 0.5    to the left,  agree=0.586, adj=0.008, (0 split)
## 
## Node number 6: 3262 observations,    complexity param=0.003346517
##   predicted class=B1  expected loss=0.5012262  P(node) =0.1631
##     class counts:  1627  1049   415   155    16
##    probabilities: 0.499 0.322 0.127 0.048 0.005 
##   left son=12 (1087 obs) right son=13 (2175 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=22.12235, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=18.39133, (0 missing)
##       kidney            < 0.5    to the left,  improve=16.45818, (0 missing)
##       reimbursement2008 < 2535   to the left,  improve=15.04368, (0 missing)
##       arthritis         < 0.5    to the left,  improve=14.50169, (0 missing)
## 
## Node number 7: 4596 observations,    complexity param=0.01703681
##   predicted class=B2  expected loss=0.6037859  P(node) =0.2298
##     class counts:  1206  1821   941   548    80
##    probabilities: 0.262 0.396 0.205 0.119 0.017 
##   left son=14 (1002 obs) right son=15 (3594 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=54.64315, (0 missing)
##       kidney            < 0.5    to the left,  improve=39.83945, (0 missing)
##       arthritis         < 0.5    to the left,  improve=27.98163, (0 missing)
##       ihd               < 0.5    to the left,  improve=27.96369, (0 missing)
##       reimbursement2008 < 14985  to the left,  improve=24.59678, (0 missing)
## 
## Node number 10: 2374 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1693345  P(node) =0.1187
##     class counts:  1972   239   123    35     5
##    probabilities: 0.831 0.101 0.052 0.015 0.002 
##   left son=20 (1860 obs) right son=21 (514 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=2.303753, (0 missing)
##       reimbursement2008 < 415    to the left,  improve=1.555073, (0 missing)
##       age               < 89.5   to the left,  improve=1.295020, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.286801, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.280980, (0 missing)
## 
## Node number 11: 3312 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.2844203  P(node) =0.1656
##     class counts:  2370   586   241   104    11
##    probabilities: 0.716 0.177 0.073 0.031 0.003 
##   left son=22 (1722 obs) right son=23 (1590 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=7.957796, (0 missing)
##       diabetes          < 0.5    to the left,  improve=6.966093, (0 missing)
##       reimbursement2008 < 1185   to the left,  improve=5.843071, (0 missing)
##       kidney            < 0.5    to the left,  improve=4.261749, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=4.259057, (0 missing)
##   Surrogate splits:
##       heart.failure     < 0.5    to the left,  agree=0.581, adj=0.127, (0 split)
##       diabetes          < 0.5    to the left,  agree=0.570, adj=0.104, (0 split)
##       reimbursement2008 < 1285   to the left,  agree=0.551, adj=0.065, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.542, adj=0.045, (0 split)
##       kidney            < 0.5    to the left,  agree=0.542, adj=0.045, (0 split)
## 
## Node number 12: 1087 observations,    complexity param=0.000760572
##   predicted class=B1  expected loss=0.4066237  P(node) =0.05435
##     class counts:   645   279   123    36     4
##    probabilities: 0.593 0.257 0.113 0.033 0.004 
##   left son=24 (941 obs) right son=25 (146 obs)
##   Primary splits:
##       kidney        < 0.5    to the left,  improve=6.950529, (0 missing)
##       heart.failure < 0.5    to the left,  improve=5.539453, (0 missing)
##       copd          < 0.5    to the left,  improve=3.363659, (0 missing)
##       diabetes      < 0.5    to the left,  improve=3.245895, (0 missing)
##       osteoporosis  < 0.5    to the left,  improve=2.285942, (0 missing)
## 
## Node number 13: 2175 observations,    complexity param=0.003346517
##   predicted class=B1  expected loss=0.5485057  P(node) =0.10875
##     class counts:   982   770   292   119    12
##    probabilities: 0.451 0.354 0.134 0.055 0.006 
##   left son=26 (1275 obs) right son=27 (900 obs)
##   Primary splits:
##       reimbursement2008 < 2515   to the left,  improve=11.475830, (0 missing)
##       arthritis         < 0.5    to the left,  improve=10.277840, (0 missing)
##       heart.failure     < 0.5    to the left,  improve= 7.801216, (0 missing)
##       kidney            < 0.5    to the left,  improve= 7.393483, (0 missing)
##       bucket2008        < 1.5    to the left,  improve= 6.716155, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.762, adj=0.426, (0 split)
##       copd       < 0.5    to the left,  agree=0.592, adj=0.013, (0 split)
##       age        < 33     to the right, agree=0.590, adj=0.010, (0 split)
## 
## Node number 14: 1002 observations,    complexity param=0.005019775
##   predicted class=B1  expected loss=0.5568862  P(node) =0.0501
##     class counts:   444   332   169    54     3
##    probabilities: 0.443 0.331 0.169 0.054 0.003 
##   left son=28 (682 obs) right son=29 (320 obs)
##   Primary splits:
##       depression   < 0.5    to the left,  improve=13.412950, (0 missing)
##       cancer       < 0.5    to the left,  improve= 8.676806, (0 missing)
##       osteoporosis < 0.5    to the left,  improve= 6.334493, (0 missing)
##       arthritis    < 0.5    to the left,  improve= 6.023249, (0 missing)
##       ihd          < 0.5    to the left,  improve= 5.212491, (0 missing)
##   Surrogate splits:
##       age < 49.5   to the right, agree=0.682, adj=0.003, (0 split)
## 
## Node number 15: 3594 observations,    complexity param=0.0008746577
##   predicted class=B2  expected loss=0.5856984  P(node) =0.1797
##     class counts:   762  1489   772   494    77
##    probabilities: 0.212 0.414 0.215 0.137 0.021 
##   left son=30 (1568 obs) right son=31 (2026 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=29.54937, (0 missing)
##       reimbursement2008 < 14405  to the left,  improve=18.69161, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=16.83945, (0 missing)
##       arthritis         < 0.5    to the left,  improve=15.87697, (0 missing)
##       ihd               < 0.5    to the left,  improve=11.13037, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 7325   to the left,  agree=0.660, adj=0.220, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.658, adj=0.217, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.633, adj=0.159, (0 split)
##       ihd               < 0.5    to the left,  agree=0.598, adj=0.078, (0 split)
##       copd              < 0.5    to the left,  agree=0.593, adj=0.067, (0 split)
## 
## Node number 20: 1860 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1553763  P(node) =0.093
##     class counts:  1571   176    86    23     4
##    probabilities: 0.845 0.095 0.046 0.012 0.002 
##   left son=40 (1774 obs) right son=41 (86 obs)
##   Primary splits:
##       age               < 89.5   to the left,  improve=1.8556120, (0 missing)
##       reimbursement2008 < 665    to the left,  improve=0.6577829, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.6342891, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5532770, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5456541, (0 missing)
## 
## Node number 21: 514 observations,    complexity param=5.07048e-05
##   predicted class=B1  expected loss=0.2198444  P(node) =0.0257
##     class counts:   401    63    37    12     1
##    probabilities: 0.780 0.123 0.072 0.023 0.002 
##   left son=42 (173 obs) right son=43 (341 obs)
##   Primary splits:
##       reimbursement2008 < 425    to the left,  improve=1.4829330, (0 missing)
##       age               < 94.5   to the right, improve=0.8488381, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5210342, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.4383554, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.3942705, (0 missing)
##   Surrogate splits:
##       age < 98.5   to the right, agree=0.671, adj=0.023, (0 split)
## 
## Node number 22: 1722 observations,    complexity param=0.0001303838
##   predicted class=B1  expected loss=0.2462253  P(node) =0.0861
##     class counts:  1298   261   107    51     5
##    probabilities: 0.754 0.152 0.062 0.030 0.003 
##   left son=44 (951 obs) right son=45 (771 obs)
##   Primary splits:
##       reimbursement2008 < 1085   to the left,  improve=2.133022, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.851709, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.814680, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.791298, (0 missing)
##       depression        < 0.5    to the left,  improve=1.477471, (0 missing)
##   Surrogate splits:
##       kidney       < 0.5    to the left,  agree=0.569, adj=0.038, (0 split)
##       osteoporosis < 0.5    to the left,  agree=0.562, adj=0.022, (0 split)
##       arthritis    < 0.5    to the left,  agree=0.560, adj=0.017, (0 split)
##       diabetes     < 0.5    to the left,  agree=0.560, adj=0.017, (0 split)
##       depression   < 0.5    to the left,  agree=0.559, adj=0.016, (0 split)
## 
## Node number 23: 1590 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.3257862  P(node) =0.0795
##     class counts:  1072   325   134    53     6
##    probabilities: 0.674 0.204 0.084 0.033 0.004 
##   left son=46 (771 obs) right son=47 (819 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=3.574744, (0 missing)
##       reimbursement2008 < 1285   to the left,  improve=3.467285, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=2.297182, (0 missing)
##       age               < 27.5   to the right, improve=1.741472, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.681255, (0 missing)
##   Surrogate splits:
##       heart.failure     < 0.5    to the left,  agree=0.550, adj=0.073, (0 split)
##       reimbursement2008 < 1145   to the left,  agree=0.545, adj=0.061, (0 split)
##       kidney            < 0.5    to the left,  agree=0.535, adj=0.040, (0 split)
##       age               < 76.5   to the left,  agree=0.528, adj=0.026, (0 split)
##       depression        < 0.5    to the left,  agree=0.522, adj=0.014, (0 split)
## 
## Node number 24: 941 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.3804463  P(node) =0.04705
##     class counts:   583   229    96    29     4
##    probabilities: 0.620 0.243 0.102 0.031 0.004 
##   left son=48 (680 obs) right son=49 (261 obs)
##   Primary splits:
##       heart.failure < 0.5    to the left,  improve=4.641423, (0 missing)
##       diabetes      < 0.5    to the left,  improve=2.866491, (0 missing)
##       osteoporosis  < 0.5    to the left,  improve=1.985004, (0 missing)
##       copd          < 0.5    to the left,  improve=1.760285, (0 missing)
##       age           < 52.5   to the left,  improve=1.424379, (0 missing)
## 
## Node number 25: 146 observations,    complexity param=0.000760572
##   predicted class=B1  expected loss=0.5753425  P(node) =0.0073
##     class counts:    62    50    27     7     0
##    probabilities: 0.425 0.342 0.185 0.048 0.000 
##   left son=50 (82 obs) right son=51 (64 obs)
##   Primary splits:
##       age               < 74.5   to the left,  improve=3.6513430, (0 missing)
##       reimbursement2008 < 3080   to the right, improve=2.1345630, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.2427630, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.0530420, (0 missing)
##       copd              < 0.5    to the left,  improve=0.9560376, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1765   to the right, agree=0.575, adj=0.031, (0 split)
## 
## Node number 26: 1275 observations,    complexity param=0.001064801
##   predicted class=B1  expected loss=0.4996078  P(node) =0.06375
##     class counts:   638   409   152    68     8
##    probabilities: 0.500 0.321 0.119 0.053 0.006 
##   left son=52 (880 obs) right son=53 (395 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=5.193576, (0 missing)
##       reimbursement2008 < 1765   to the left,  improve=4.667403, (0 missing)
##       age               < 80.5   to the right, improve=3.217982, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=2.254540, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.756421, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2495   to the left,  agree=0.693, adj=0.008, (0 split)
## 
## Node number 27: 900 observations,    complexity param=0.003346517
##   predicted class=B2  expected loss=0.5988889  P(node) =0.045
##     class counts:   344   361   140    51     4
##    probabilities: 0.382 0.401 0.156 0.057 0.004 
##   left son=54 (614 obs) right son=55 (286 obs)
##   Primary splits:
##       arthritis     < 0.5    to the left,  improve=9.449426, (0 missing)
##       heart.failure < 0.5    to the left,  improve=7.177110, (0 missing)
##       kidney        < 0.5    to the left,  improve=4.982522, (0 missing)
##       copd          < 0.5    to the left,  improve=3.774501, (0 missing)
##       cancer        < 0.5    to the left,  improve=3.018782, (0 missing)
##   Surrogate splits:
##       age < 37.5   to the right, agree=0.687, adj=0.014, (0 split)
## 
## Node number 28: 682 observations,    complexity param=0.001216915
##   predicted class=B1  expected loss=0.4912023  P(node) =0.0341
##     class counts:   347   202    97    33     3
##    probabilities: 0.509 0.296 0.142 0.048 0.004 
##   left son=56 (563 obs) right son=57 (119 obs)
##   Primary splits:
##       cancer            < 0.5    to the left,  improve=8.288699, (0 missing)
##       arthritis         < 0.5    to the left,  improve=4.176438, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=3.934963, (0 missing)
##       ihd               < 0.5    to the left,  improve=3.166893, (0 missing)
##       reimbursement2008 < 8450   to the right, improve=2.733079, (0 missing)
## 
## Node number 29: 320 observations,    complexity param=0.0008619815
##   predicted class=B2  expected loss=0.59375  P(node) =0.016
##     class counts:    97   130    72    21     0
##    probabilities: 0.303 0.406 0.225 0.066 0.000 
##   left son=58 (213 obs) right son=59 (107 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.166497, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.990034, (0 missing)
##       age               < 91.5   to the right, improve=1.926250, (0 missing)
##       reimbursement2008 < 3710   to the left,  improve=1.809690, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.730409, (0 missing)
##   Surrogate splits:
##       stroke            < 0.5    to the left,  agree=0.678, adj=0.037, (0 split)
##       reimbursement2008 < 40240  to the left,  agree=0.675, adj=0.028, (0 split)
##       age               < 42.5   to the right, agree=0.672, adj=0.019, (0 split)
##       bucket2008        < 4.5    to the left,  agree=0.669, adj=0.009, (0 split)
## 
## Node number 30: 1568 observations,    complexity param=0.0008746577
##   predicted class=B2  expected loss=0.5612245  P(node) =0.0784
##     class counts:   448   688   304   117    11
##    probabilities: 0.286 0.439 0.194 0.075 0.007 
##   left son=60 (964 obs) right son=61 (604 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=9.229921, (0 missing)
##       cancer            < 0.5    to the left,  improve=6.469383, (0 missing)
##       reimbursement2008 < 59995  to the left,  improve=4.836546, (0 missing)
##       bucket2008        < 4.5    to the left,  improve=3.876636, (0 missing)
##       age               < 71.5   to the right, improve=3.803969, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 35170  to the left,  agree=0.620, adj=0.013, (0 split)
##       bucket2008        < 4.5    to the left,  agree=0.615, adj=0.002, (0 split)
## 
## Node number 31: 2026 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6046397  P(node) =0.1013
##     class counts:   314   801   468   377    66
##    probabilities: 0.155 0.395 0.231 0.186 0.033 
##   left son=62 (1090 obs) right son=63 (936 obs)
##   Primary splits:
##       reimbursement2008 < 15095  to the left,  improve=9.838861, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=7.625303, (0 missing)
##       arthritis         < 0.5    to the left,  improve=7.497489, (0 missing)
##       ihd               < 0.5    to the left,  improve=4.354999, (0 missing)
##       age               < 44.5   to the right, improve=4.056220, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the left,  agree=0.913, adj=0.811, (0 split)
##       copd       < 0.5    to the left,  agree=0.610, adj=0.156, (0 split)
##       stroke     < 0.5    to the left,  agree=0.582, adj=0.096, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.567, adj=0.063, (0 split)
##       cancer     < 0.5    to the left,  agree=0.566, adj=0.061, (0 split)
## 
## Node number 40: 1774 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1499436  P(node) =0.0887
##     class counts:  1508   165    75    23     3
##    probabilities: 0.850 0.093 0.042 0.013 0.002 
##   left son=80 (1764 obs) right son=81 (10 obs)
##   Primary splits:
##       age               < 29.5   to the right, improve=1.1538870, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8525277, (0 missing)
##       reimbursement2008 < 665    to the left,  improve=0.6307025, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5616328, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5123385, (0 missing)
## 
## Node number 41: 86 observations
##   predicted class=B1  expected loss=0.2674419  P(node) =0.0043
##     class counts:    63    11    11     0     1
##    probabilities: 0.733 0.128 0.128 0.000 0.012 
## 
## Node number 42: 173 observations,    complexity param=5.07048e-05
##   predicted class=B1  expected loss=0.1618497  P(node) =0.00865
##     class counts:   145    13    11     4     0
##    probabilities: 0.838 0.075 0.064 0.023 0.000 
##   left son=84 (147 obs) right son=85 (26 obs)
##   Primary splits:
##       age               < 64.5   to the right, improve=2.0458370, (0 missing)
##       reimbursement2008 < 355    to the right, improve=0.9835129, (0 missing)
##       depression        < 0.5    to the right, improve=0.3524686, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.3137783, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.2903122, (0 missing)
## 
## Node number 43: 341 observations
##   predicted class=B1  expected loss=0.2492669  P(node) =0.01705
##     class counts:   256    50    26     8     1
##    probabilities: 0.751 0.147 0.076 0.023 0.003 
## 
## Node number 44: 951 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2197687  P(node) =0.04755
##     class counts:   742   132    48    26     3
##    probabilities: 0.780 0.139 0.050 0.027 0.003 
##   left son=88 (811 obs) right son=89 (140 obs)
##   Primary splits:
##       alzheimers    < 0.5    to the left,  improve=1.2963180, (0 missing)
##       depression    < 0.5    to the left,  improve=1.1750410, (0 missing)
##       kidney        < 0.5    to the left,  improve=0.8204364, (0 missing)
##       diabetes      < 0.5    to the left,  improve=0.8186009, (0 missing)
##       heart.failure < 0.5    to the left,  improve=0.6649241, (0 missing)
## 
## Node number 45: 771 observations,    complexity param=0.0001303838
##   predicted class=B1  expected loss=0.2788586  P(node) =0.03855
##     class counts:   556   129    59    25     2
##    probabilities: 0.721 0.167 0.077 0.032 0.003 
##   left son=90 (758 obs) right son=91 (13 obs)
##   Primary splits:
##       stroke       < 0.5    to the left,  improve=2.8198560, (0 missing)
##       osteoporosis < 0.5    to the left,  improve=1.3510390, (0 missing)
##       age          < 67.5   to the right, improve=1.2269310, (0 missing)
##       diabetes     < 0.5    to the left,  improve=0.9157286, (0 missing)
##       kidney       < 0.5    to the left,  improve=0.7050616, (0 missing)
## 
## Node number 46: 771 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.2853437  P(node) =0.03855
##     class counts:   551   139    60    17     4
##    probabilities: 0.715 0.180 0.078 0.022 0.005 
##   left son=92 (713 obs) right son=93 (58 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=2.3312380, (0 missing)
##       reimbursement2008 < 1465   to the left,  improve=1.5865660, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.3286190, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.1740950, (0 missing)
##       age               < 39.5   to the right, improve=0.8807352, (0 missing)
## 
## Node number 47: 819 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.3638584  P(node) =0.04095
##     class counts:   521   186    74    36     2
##    probabilities: 0.636 0.227 0.090 0.044 0.002 
##   left son=94 (412 obs) right son=95 (407 obs)
##   Primary splits:
##       reimbursement2008 < 1155   to the left,  improve=4.0618270, (0 missing)
##       age               < 96.5   to the left,  improve=1.8771670, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.1124860, (0 missing)
##       depression        < 0.5    to the left,  improve=0.8927430, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.8149295, (0 missing)
##   Surrogate splits:
##       depression    < 0.5    to the left,  agree=0.537, adj=0.069, (0 split)
##       arthritis     < 0.5    to the left,  agree=0.535, adj=0.064, (0 split)
##       age           < 75.5   to the right, agree=0.530, adj=0.054, (0 split)
##       copd          < 0.5    to the left,  agree=0.523, adj=0.039, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.521, adj=0.037, (0 split)
## 
## Node number 48: 680 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.3441176  P(node) =0.034
##     class counts:   446   153    59    20     2
##    probabilities: 0.656 0.225 0.087 0.029 0.003 
##   left son=96 (524 obs) right son=97 (156 obs)
##   Primary splits:
##       reimbursement2008 < 2605   to the left,  improve=2.7829410, (0 missing)
##       age               < 96.5   to the left,  improve=1.1143550, (0 missing)
##       copd              < 0.5    to the left,  improve=1.0550180, (0 missing)
##       depression        < 0.5    to the left,  improve=1.0401960, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.9369192, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.865, adj=0.41, (0 split)
## 
## Node number 49: 261 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.4750958  P(node) =0.01305
##     class counts:   137    76    37     9     2
##    probabilities: 0.525 0.291 0.142 0.034 0.008 
##   left son=98 (110 obs) right son=99 (151 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=2.985889, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.377857, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.334625, (0 missing)
##       reimbursement2008 < 3285   to the right, improve=1.198129, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.099034, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1845   to the left,  agree=0.613, adj=0.082, (0 split)
## 
## Node number 50: 82 observations,    complexity param=0.0006084576
##   predicted class=B1  expected loss=0.4634146  P(node) =0.0041
##     class counts:    44    22    12     4     0
##    probabilities: 0.537 0.268 0.146 0.049 0.000 
##   left son=100 (63 obs) right son=101 (19 obs)
##   Primary splits:
##       age               < 63.5   to the right, improve=2.9141960, (0 missing)
##       reimbursement2008 < 3080   to the right, improve=1.7365850, (0 missing)
##       copd              < 0.5    to the left,  improve=1.5828040, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.0929760, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.7827975, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1615   to the right, agree=0.78, adj=0.053, (0 split)
## 
## Node number 51: 64 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.5625  P(node) =0.0032
##     class counts:    18    28    15     3     0
##    probabilities: 0.281 0.438 0.234 0.047 0.000 
##   left son=102 (28 obs) right son=103 (36 obs)
##   Primary splits:
##       age               < 84.5   to the right, improve=2.3010910, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.1798210, (0 missing)
##       reimbursement2008 < 2345   to the left,  improve=0.9276332, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.6452851, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5431399, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1595   to the left,  agree=0.594, adj=0.071, (0 split)
##       depression        < 0.5    to the right, agree=0.578, adj=0.036, (0 split)
## 
## Node number 52: 880 observations,    complexity param=0.0004563432
##   predicted class=B1  expected loss=0.4681818  P(node) =0.044
##     class counts:   468   257   102    46     7
##    probabilities: 0.532 0.292 0.116 0.052 0.008 
##   left son=104 (849 obs) right son=105 (31 obs)
##   Primary splits:
##       stroke            < 0.5    to the left,  improve=3.387993, (0 missing)
##       age               < 73.5   to the right, improve=3.306641, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=3.159084, (0 missing)
##       copd              < 0.5    to the left,  improve=2.787275, (0 missing)
##       reimbursement2008 < 1855   to the left,  improve=2.780152, (0 missing)
## 
## Node number 53: 395 observations,    complexity param=0.001064801
##   predicted class=B1  expected loss=0.5696203  P(node) =0.01975
##     class counts:   170   152    50    22     1
##    probabilities: 0.430 0.385 0.127 0.056 0.003 
##   left son=106 (80 obs) right son=107 (315 obs)
##   Primary splits:
##       age               < 84.5   to the right, improve=3.498056, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=2.462798, (0 missing)
##       reimbursement2008 < 1760   to the left,  improve=2.298825, (0 missing)
##       cancer            < 0.5    to the left,  improve=2.009374, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.079384, (0 missing)
## 
## Node number 54: 614 observations,    complexity param=0.002053544
##   predicted class=B1  expected loss=0.5684039  P(node) =0.0307
##     class counts:   265   216    94    37     2
##    probabilities: 0.432 0.352 0.153 0.060 0.003 
##   left son=108 (317 obs) right son=109 (297 obs)
##   Primary splits:
##       heart.failure < 0.5    to the left,  improve=5.706356, (0 missing)
##       cancer        < 0.5    to the left,  improve=3.620611, (0 missing)
##       kidney        < 0.5    to the left,  improve=2.718926, (0 missing)
##       diabetes      < 0.5    to the left,  improve=2.388979, (0 missing)
##       stroke        < 0.5    to the left,  improve=2.007035, (0 missing)
##   Surrogate splits:
##       diabetes   < 0.5    to the left,  agree=0.593, adj=0.158, (0 split)
##       copd       < 0.5    to the left,  agree=0.570, adj=0.111, (0 split)
##       kidney     < 0.5    to the left,  agree=0.559, adj=0.088, (0 split)
##       age        < 86.5   to the left,  agree=0.550, adj=0.071, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.542, adj=0.054, (0 split)
## 
## Node number 55: 286 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.493007  P(node) =0.0143
##     class counts:    79   145    46    14     2
##    probabilities: 0.276 0.507 0.161 0.049 0.007 
##   left son=110 (174 obs) right son=111 (112 obs)
##   Primary splits:
##       reimbursement2008 < 3015   to the left,  improve=3.399972, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=2.660008, (0 missing)
##       copd              < 0.5    to the left,  improve=1.954436, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.720664, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.503497, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.972, adj=0.929, (0 split)
##       age        < 47.5   to the right, agree=0.612, adj=0.009, (0 split)
## 
## Node number 56: 563 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.4476021  P(node) =0.02815
##     class counts:   311   158    71    20     3
##    probabilities: 0.552 0.281 0.126 0.036 0.005 
##   left son=112 (419 obs) right son=113 (144 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=4.749310, (0 missing)
##       ihd               < 0.5    to the left,  improve=4.117879, (0 missing)
##       reimbursement2008 < 8450   to the right, improve=2.969907, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=2.407056, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=2.354174, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 3465   to the right, agree=0.746, adj=0.007, (0 split)
## 
## Node number 57: 119 observations,    complexity param=0.0009126863
##   predicted class=B2  expected loss=0.6302521  P(node) =0.00595
##     class counts:    36    44    26    13     0
##    probabilities: 0.303 0.370 0.218 0.109 0.000 
##   left son=114 (55 obs) right son=115 (64 obs)
##   Primary splits:
##       reimbursement2008 < 6095   to the left,  improve=1.638928, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.623836, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.588552, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.103598, (0 missing)
##       copd              < 0.5    to the left,  improve=1.082200, (0 missing)
##   Surrogate splits:
##       bucket2008    < 2.5    to the left,  agree=0.798, adj=0.564, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.689, adj=0.327, (0 split)
##       ihd           < 0.5    to the left,  agree=0.655, adj=0.255, (0 split)
##       age           < 72.5   to the left,  agree=0.580, adj=0.091, (0 split)
##       kidney        < 0.5    to the left,  agree=0.580, adj=0.091, (0 split)
## 
## Node number 58: 213 observations,    complexity param=0.0008619815
##   predicted class=B2  expected loss=0.6056338  P(node) =0.01065
##     class counts:    75    84    42    12     0
##    probabilities: 0.352 0.394 0.197 0.056 0.000 
##   left son=116 (20 obs) right son=117 (193 obs)
##   Primary splits:
##       age               < 55.5   to the left,  improve=2.485799, (0 missing)
##       reimbursement2008 < 9080   to the right, improve=1.923864, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.913762, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.732394, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.683900, (0 missing)
## 
## Node number 59: 107 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.5700935  P(node) =0.00535
##     class counts:    22    46    30     9     0
##    probabilities: 0.206 0.430 0.280 0.084 0.000 
##   left son=118 (13 obs) right son=119 (94 obs)
##   Primary splits:
##       reimbursement2008 < 25420  to the right, improve=1.3314010, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.1104610, (0 missing)
##       age               < 87.5   to the left,  improve=0.9520085, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.6222856, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.6046879, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.953, adj=0.615, (0 split)
## 
## Node number 60: 964 observations,    complexity param=0.0008746577
##   predicted class=B2  expected loss=0.5923237  P(node) =0.0482
##     class counts:   324   393   182    60     5
##    probabilities: 0.336 0.408 0.189 0.062 0.005 
##   left son=120 (791 obs) right son=121 (173 obs)
##   Primary splits:
##       cancer            < 0.5    to the left,  improve=7.881057, (0 missing)
##       age               < 70.5   to the left,  improve=5.309810, (0 missing)
##       reimbursement2008 < 58515  to the left,  improve=5.164127, (0 missing)
##       bucket2008        < 4.5    to the left,  improve=4.128531, (0 missing)
##       ihd               < 0.5    to the left,  improve=3.548552, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 70655  to the left,  agree=0.823, adj=0.012, (0 split)
## 
## Node number 61: 604 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5115894  P(node) =0.0302
##     class counts:   124   295   122    57     6
##    probabilities: 0.205 0.488 0.202 0.094 0.010 
##   left son=122 (69 obs) right son=123 (535 obs)
##   Primary splits:
##       reimbursement2008 < 3875   to the left,  improve=3.786294, (0 missing)
##       depression        < 0.5    to the left,  improve=2.941959, (0 missing)
##       age               < 34     to the right, improve=1.969721, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.555014, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.351079, (0 missing)
## 
## Node number 62: 1090 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.5752294  P(node) =0.0545
##     class counts:   195   463   261   148    23
##    probabilities: 0.179 0.425 0.239 0.136 0.021 
##   left son=124 (638 obs) right son=125 (452 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=7.151203, (0 missing)
##       reimbursement2008 < 5655   to the left,  improve=3.223904, (0 missing)
##       ihd               < 0.5    to the left,  improve=2.644429, (0 missing)
##       age               < 44.5   to the right, improve=2.630564, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.756050, (0 missing)
##   Surrogate splits:
##       age < 29.5   to the right, agree=0.589, adj=0.009, (0 split)
## 
## Node number 63: 936 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6388889  P(node) =0.0468
##     class counts:   119   338   207   229    43
##    probabilities: 0.127 0.361 0.221 0.245 0.046 
##   left son=126 (53 obs) right son=127 (883 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=2.996452, (0 missing)
##       reimbursement2008 < 26375  to the left,  improve=2.908218, (0 missing)
##       age               < 65.5   to the right, improve=2.302986, (0 missing)
##       copd              < 0.5    to the left,  improve=2.090686, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.919244, (0 missing)
## 
## Node number 80: 1764 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1485261  P(node) =0.0882
##     class counts:  1502   162    75    22     3
##    probabilities: 0.851 0.092 0.043 0.012 0.002 
##   left son=160 (1586 obs) right son=161 (178 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=0.9323517, (0 missing)
##       age               < 71.5   to the left,  improve=0.7839176, (0 missing)
##       reimbursement2008 < 665    to the left,  improve=0.6933809, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5712541, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5496311, (0 missing)
## 
## Node number 81: 10 observations
##   predicted class=B1  expected loss=0.4  P(node) =0.0005
##     class counts:     6     3     0     1     0
##    probabilities: 0.600 0.300 0.000 0.100 0.000 
## 
## Node number 84: 147 observations
##   predicted class=B1  expected loss=0.122449  P(node) =0.00735
##     class counts:   129     9     7     2     0
##    probabilities: 0.878 0.061 0.048 0.014 0.000 
## 
## Node number 85: 26 observations,    complexity param=5.07048e-05
##   predicted class=B1  expected loss=0.3846154  P(node) =0.0013
##     class counts:    16     4     4     2     0
##    probabilities: 0.615 0.154 0.154 0.077 0.000 
##   left son=170 (19 obs) right son=171 (7 obs)
##   Primary splits:
##       reimbursement2008 < 250    to the right, improve=1.9872760, (0 missing)
##       age               < 56.5   to the left,  improve=0.3934732, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.3076923, (0 missing)
## 
## Node number 88: 811 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2083847  P(node) =0.04055
##     class counts:   642   105    38    24     2
##    probabilities: 0.792 0.129 0.047 0.030 0.002 
##   left son=176 (544 obs) right son=177 (267 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=1.0063530, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9333841, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.7386915, (0 missing)
##       reimbursement2008 < 905    to the left,  improve=0.5328549, (0 missing)
##       age               < 95     to the right, improve=0.4748885, (0 missing)
##   Surrogate splits:
##       kidney            < 0.5    to the left,  agree=0.691, adj=0.060, (0 split)
##       copd              < 0.5    to the left,  agree=0.684, adj=0.041, (0 split)
##       reimbursement2008 < 1075   to the left,  agree=0.677, adj=0.019, (0 split)
##       stroke            < 0.5    to the left,  agree=0.676, adj=0.015, (0 split)
##       age               < 98.5   to the left,  agree=0.672, adj=0.004, (0 split)
## 
## Node number 89: 140 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2857143  P(node) =0.007
##     class counts:   100    27    10     2     1
##    probabilities: 0.714 0.193 0.071 0.014 0.007 
##   left son=178 (133 obs) right son=179 (7 obs)
##   Primary splits:
##       age               < 91.5   to the left,  improve=1.9225560, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.7529606, (0 missing)
##       reimbursement2008 < 715    to the left,  improve=0.6604396, (0 missing)
##       copd              < 0.5    to the right, improve=0.5219780, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.5090226, (0 missing)
## 
## Node number 90: 758 observations,    complexity param=0.0001303838
##   predicted class=B1  expected loss=0.2730871  P(node) =0.0379
##     class counts:   551   126    54    25     2
##    probabilities: 0.727 0.166 0.071 0.033 0.003 
##   left son=180 (586 obs) right son=181 (172 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=1.4527870, (0 missing)
##       age               < 67.5   to the right, improve=1.2745370, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.1236350, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.8891357, (0 missing)
##       reimbursement2008 < 1125   to the right, improve=0.6899320, (0 missing)
## 
## Node number 91: 13 observations
##   predicted class=B1  expected loss=0.6153846  P(node) =0.00065
##     class counts:     5     3     5     0     0
##    probabilities: 0.385 0.231 0.385 0.000 0.000 
## 
## Node number 92: 713 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.2720898  P(node) =0.03565
##     class counts:   519   125    51    14     4
##    probabilities: 0.728 0.175 0.072 0.020 0.006 
##   left son=184 (691 obs) right son=185 (22 obs)
##   Primary splits:
##       age               < 39.5   to the right, improve=1.1668370, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.1390500, (0 missing)
##       reimbursement2008 < 1465   to the left,  improve=0.9813589, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.5722300, (0 missing)
##       cancer            < 0.5    to the right, improve=0.3196481, (0 missing)
## 
## Node number 93: 58 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4482759  P(node) =0.0029
##     class counts:    32    14     9     3     0
##    probabilities: 0.552 0.241 0.155 0.052 0.000 
##   left son=186 (15 obs) right son=187 (43 obs)
##   Primary splits:
##       age               < 69.5   to the left,  improve=3.2494520, (0 missing)
##       arthritis         < 0.5    to the left,  improve=2.0076310, (0 missing)
##       reimbursement2008 < 1420   to the left,  improve=1.5737930, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7189879, (0 missing)
##       depression        < 0.5    to the right, improve=0.5328407, (0 missing)
## 
## Node number 94: 412 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3058252  P(node) =0.0206
##     class counts:   286    79    34    12     1
##    probabilities: 0.694 0.192 0.083 0.029 0.002 
##   left son=188 (90 obs) right son=189 (322 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=1.7905600, (0 missing)
##       kidney            < 0.5    to the right, improve=1.1304480, (0 missing)
##       reimbursement2008 < 845    to the right, improve=1.0921920, (0 missing)
##       age               < 46.5   to the right, improve=0.8862043, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.6585376, (0 missing)
## 
## Node number 95: 407 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4226044  P(node) =0.02035
##     class counts:   235   107    40    24     1
##    probabilities: 0.577 0.263 0.098 0.059 0.002 
##   left son=190 (382 obs) right son=191 (25 obs)
##   Primary splits:
##       age               < 89.5   to the left,  improve=2.713552, (0 missing)
##       reimbursement2008 < 1175   to the right, improve=1.792258, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.783573, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.289334, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.141444, (0 missing)
## 
## Node number 96: 524 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.3282443  P(node) =0.0262
##     class counts:   352   103    52    16     1
##    probabilities: 0.672 0.197 0.099 0.031 0.002 
##   left son=192 (517 obs) right son=193 (7 obs)
##   Primary splits:
##       age               < 96.5   to the left,  improve=1.6925650, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.3207170, (0 missing)
##       depression        < 0.5    to the left,  improve=1.3189090, (0 missing)
##       copd              < 0.5    to the left,  improve=1.0179070, (0 missing)
##       reimbursement2008 < 2555   to the right, improve=0.9997021, (0 missing)
## 
## Node number 97: 156 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.3974359  P(node) =0.0078
##     class counts:    94    50     7     4     1
##    probabilities: 0.603 0.321 0.045 0.026 0.006 
##   left son=194 (118 obs) right son=195 (38 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=3.3295250, (0 missing)
##       age               < 71.5   to the left,  improve=1.4519230, (0 missing)
##       reimbursement2008 < 2805   to the right, improve=1.4487180, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.1881170, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4811752, (0 missing)
## 
## Node number 98: 110 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.3818182  P(node) =0.0055
##     class counts:    68    26     9     6     1
##    probabilities: 0.618 0.236 0.082 0.055 0.009 
##   left son=196 (32 obs) right son=197 (78 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=1.5659670, (0 missing)
##       reimbursement2008 < 1805   to the right, improve=1.4835180, (0 missing)
##       age               < 65     to the left,  improve=1.0413730, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.8202845, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.5535759, (0 missing)
##   Surrogate splits:
##       copd       < 0.5    to the right, agree=0.727, adj=0.063, (0 split)
##       age        < 87.5   to the right, agree=0.718, adj=0.031, (0 split)
##       alzheimers < 0.5    to the right, agree=0.718, adj=0.031, (0 split)
## 
## Node number 99: 151 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.5430464  P(node) =0.00755
##     class counts:    69    50    28     3     1
##    probabilities: 0.457 0.331 0.185 0.020 0.007 
##   left son=198 (140 obs) right son=199 (11 obs)
##   Primary splits:
##       reimbursement2008 < 1675   to the right, improve=1.6192660, (0 missing)
##       age               < 79.5   to the left,  improve=1.2019600, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.1347180, (0 missing)
##       arthritis         < 0.5    to the right, improve=1.0828460, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.7387061, (0 missing)
## 
## Node number 100: 63 observations
##   predicted class=B1  expected loss=0.3968254  P(node) =0.00315
##     class counts:    38    12     9     4     0
##    probabilities: 0.603 0.190 0.143 0.063 0.000 
## 
## Node number 101: 19 observations
##   predicted class=B2  expected loss=0.4736842  P(node) =0.00095
##     class counts:     6    10     3     0     0
##    probabilities: 0.316 0.526 0.158 0.000 0.000 
## 
## Node number 102: 28 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.0014
##     class counts:     9    16     2     1     0
##    probabilities: 0.321 0.571 0.071 0.036 0.000 
## 
## Node number 103: 36 observations,    complexity param=0.000507048
##   predicted class=B3  expected loss=0.6388889  P(node) =0.0018
##     class counts:     9    12    13     2     0
##    probabilities: 0.250 0.333 0.361 0.056 0.000 
##   left son=206 (10 obs) right son=207 (26 obs)
##   Primary splits:
##       reimbursement2008 < 1990   to the left,  improve=2.3444440, (0 missing)
##       age               < 78.5   to the left,  improve=1.6694440, (0 missing)
##       depression        < 0.5    to the right, improve=1.5277780, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.9801587, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3518519, (0 missing)
## 
## Node number 104: 849 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.459364  P(node) =0.04245
##     class counts:   459   246    92    45     7
##    probabilities: 0.541 0.290 0.108 0.053 0.008 
##   left son=208 (406 obs) right son=209 (443 obs)
##   Primary splits:
##       age               < 73.5   to the right, improve=4.000432, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=3.247702, (0 missing)
##       reimbursement2008 < 1855   to the left,  improve=2.540980, (0 missing)
##       kidney            < 0.5    to the left,  improve=2.518808, (0 missing)
##       copd              < 0.5    to the left,  improve=2.326450, (0 missing)
##   Surrogate splits:
##       osteoporosis      < 0.5    to the right, agree=0.541, adj=0.039, (0 split)
##       reimbursement2008 < 2215   to the right, agree=0.537, adj=0.032, (0 split)
##       heart.failure     < 0.5    to the right, agree=0.527, adj=0.010, (0 split)
## 
## Node number 105: 31 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6451613  P(node) =0.00155
##     class counts:     9    11    10     1     0
##    probabilities: 0.290 0.355 0.323 0.032 0.000 
##   left son=210 (17 obs) right son=211 (14 obs)
##   Primary splits:
##       age               < 75.5   to the right, improve=1.5871510, (0 missing)
##       reimbursement2008 < 2370   to the left,  improve=1.1497190, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5679117, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.5234255, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.3567588, (0 missing)
##   Surrogate splits:
##       osteoporosis      < 0.5    to the left,  agree=0.677, adj=0.286, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.581, adj=0.071, (0 split)
##       kidney            < 0.5    to the left,  agree=0.581, adj=0.071, (0 split)
##       reimbursement2008 < 2035   to the right, agree=0.581, adj=0.071, (0 split)
## 
## Node number 106: 80 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.425  P(node) =0.004
##     class counts:    46    23     5     6     0
##    probabilities: 0.575 0.287 0.062 0.075 0.000 
##   left son=212 (55 obs) right son=213 (25 obs)
##   Primary splits:
##       age               < 93.5   to the left,  improve=2.611364, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.487349, (0 missing)
##       reimbursement2008 < 2125   to the right, improve=1.457423, (0 missing)
##       stroke            < 0.5    to the right, improve=1.369444, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.209632, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.7, adj=0.04, (0 split)
## 
## Node number 107: 315 observations,    complexity param=0.001064801
##   predicted class=B2  expected loss=0.5904762  P(node) =0.01575
##     class counts:   124   129    45    16     1
##    probabilities: 0.394 0.410 0.143 0.051 0.003 
##   left son=214 (298 obs) right son=215 (17 obs)
##   Primary splits:
##       cancer            < 0.5    to the left,  improve=2.959923, (0 missing)
##       age               < 71.5   to the left,  improve=2.862764, (0 missing)
##       reimbursement2008 < 1705   to the left,  improve=2.440816, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.340605, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.203641, (0 missing)
## 
## Node number 108: 317 observations,    complexity param=0.002053544
##   predicted class=B1  expected loss=0.488959  P(node) =0.01585
##     class counts:   162   100    41    12     2
##    probabilities: 0.511 0.315 0.129 0.038 0.006 
##   left son=216 (281 obs) right son=217 (36 obs)
##   Primary splits:
##       cancer            < 0.5    to the left,  improve=7.0540640, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.2948500, (0 missing)
##       age               < 67.5   to the left,  improve=1.1694920, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7114914, (0 missing)
##       reimbursement2008 < 3375   to the right, improve=0.7111587, (0 missing)
## 
## Node number 109: 297 observations,    complexity param=0.001216915
##   predicted class=B2  expected loss=0.6094276  P(node) =0.01485
##     class counts:   103   116    53    25     0
##    probabilities: 0.347 0.391 0.178 0.084 0.000 
##   left son=218 (213 obs) right son=219 (84 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=3.189782, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=2.501684, (0 missing)
##       stroke            < 0.5    to the left,  improve=2.034430, (0 missing)
##       reimbursement2008 < 2545   to the right, improve=1.945862, (0 missing)
##       copd              < 0.5    to the left,  improve=1.405257, (0 missing)
## 
## Node number 110: 174 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5574713  P(node) =0.0087
##     class counts:    54    77    36     6     1
##    probabilities: 0.310 0.443 0.207 0.034 0.006 
##   left son=220 (157 obs) right son=221 (17 obs)
##   Primary splits:
##       reimbursement2008 < 2965   to the left,  improve=2.237107, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.712199, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.626229, (0 missing)
##       age               < 66.5   to the left,  improve=1.521372, (0 missing)
##       copd              < 0.5    to the left,  improve=1.472441, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.948, adj=0.471, (0 split)
## 
## Node number 111: 112 observations,    complexity param=0.000190143
##   predicted class=B2  expected loss=0.3928571  P(node) =0.0056
##     class counts:    25    68    10     8     1
##    probabilities: 0.223 0.607 0.089 0.071 0.009 
##   left son=222 (81 obs) right son=223 (31 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=2.8140400, (0 missing)
##       age               < 88.5   to the left,  improve=1.5837910, (0 missing)
##       reimbursement2008 < 3405   to the left,  improve=1.3337910, (0 missing)
##       copd              < 0.5    to the left,  improve=1.0054300, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.8988095, (0 missing)
## 
## Node number 112: 419 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.4033413  P(node) =0.02095
##     class counts:   250   111    42    13     3
##    probabilities: 0.597 0.265 0.100 0.031 0.007 
##   left son=224 (330 obs) right son=225 (89 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=2.610752, (0 missing)
##       reimbursement2008 < 8430   to the right, improve=2.207527, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.748820, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.716918, (0 missing)
##       copd              < 0.5    to the left,  improve=1.485559, (0 missing)
## 
## Node number 113: 144 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.5763889  P(node) =0.0072
##     class counts:    61    47    29     7     0
##    probabilities: 0.424 0.326 0.201 0.049 0.000 
##   left son=226 (58 obs) right son=227 (86 obs)
##   Primary splits:
##       age               < 73.5   to the left,  improve=2.071126, (0 missing)
##       reimbursement2008 < 3585   to the right, improve=2.059784, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.866475, (0 missing)
##       copd              < 0.5    to the right, improve=1.815446, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.213565, (0 missing)
##   Surrogate splits:
##       ihd               < 0.5    to the left,  agree=0.604, adj=0.017, (0 split)
##       reimbursement2008 < 25970  to the right, agree=0.604, adj=0.017, (0 split)
## 
## Node number 114: 55 observations,    complexity param=0.000760572
##   predicted class=B1  expected loss=0.6181818  P(node) =0.00275
##     class counts:    21    15    12     7     0
##    probabilities: 0.382 0.273 0.218 0.127 0.000 
##   left son=228 (42 obs) right son=229 (13 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=4.3525140, (0 missing)
##       copd              < 0.5    to the left,  improve=1.5063600, (0 missing)
##       reimbursement2008 < 3745   to the left,  improve=1.2449130, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.0678650, (0 missing)
##       age               < 64.5   to the left,  improve=0.7169246, (0 missing)
##   Surrogate splits:
##       age < 94     to the left,  agree=0.782, adj=0.077, (0 split)
## 
## Node number 115: 64 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.546875  P(node) =0.0032
##     class counts:    15    29    14     6     0
##    probabilities: 0.234 0.453 0.219 0.094 0.000 
##   left son=230 (41 obs) right son=231 (23 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.4228860, (0 missing)
##       reimbursement2008 < 9080   to the right, improve=1.9265930, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=1.1557870, (0 missing)
##       age               < 66.5   to the right, improve=1.0320330, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.7558656, (0 missing)
##   Surrogate splits:
##       age               < 61     to the right, agree=0.672, adj=0.087, (0 split)
##       reimbursement2008 < 6480   to the right, agree=0.656, adj=0.043, (0 split)
## 
## Node number 116: 20 observations
##   predicted class=B1  expected loss=0.45  P(node) =0.001
##     class counts:    11     3     6     0     0
##    probabilities: 0.550 0.150 0.300 0.000 0.000 
## 
## Node number 117: 193 observations,    complexity param=0.0008619815
##   predicted class=B2  expected loss=0.5803109  P(node) =0.00965
##     class counts:    64    81    36    12     0
##    probabilities: 0.332 0.420 0.187 0.062 0.000 
##   left son=234 (136 obs) right son=235 (57 obs)
##   Primary splits:
##       age               < 82.5   to the left,  improve=2.821502, (0 missing)
##       cancer            < 0.5    to the left,  improve=2.768983, (0 missing)
##       reimbursement2008 < 8080   to the right, improve=2.356612, (0 missing)
##       bucket2008        < 2.5    to the right, improve=2.356612, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=2.157632, (0 missing)
## 
## Node number 118: 13 observations
##   predicted class=B3  expected loss=0.5384615  P(node) =0.00065
##     class counts:     4     3     6     0     0
##    probabilities: 0.308 0.231 0.462 0.000 0.000 
## 
## Node number 119: 94 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.5425532  P(node) =0.0047
##     class counts:    18    43    24     9     0
##    probabilities: 0.191 0.457 0.255 0.096 0.000 
##   left son=238 (8 obs) right son=239 (86 obs)
##   Primary splits:
##       reimbursement2008 < 17845  to the right, improve=2.4226870, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.0548490, (0 missing)
##       age               < 76.5   to the left,  improve=0.9148936, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.8079343, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7191072, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.968, adj=0.625, (0 split)
## 
## Node number 120: 791 observations,    complexity param=0.0008746577
##   predicted class=B2  expected loss=0.5979772  P(node) =0.03955
##     class counts:   292   318   129    48     4
##    probabilities: 0.369 0.402 0.163 0.061 0.005 
##   left son=240 (277 obs) right son=241 (514 obs)
##   Primary splits:
##       age               < 70.5   to the left,  improve=3.355752, (0 missing)
##       reimbursement2008 < 49845  to the left,  improve=3.229908, (0 missing)
##       ihd               < 0.5    to the left,  improve=2.761119, (0 missing)
##       copd              < 0.5    to the left,  improve=2.003968, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.265923, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 3445   to the left,  agree=0.655, adj=0.014, (0 split)
## 
## Node number 121: 173 observations,    complexity param=0.0005324004
##   predicted class=B2  expected loss=0.566474  P(node) =0.00865
##     class counts:    32    75    53    12     1
##    probabilities: 0.185 0.434 0.306 0.069 0.006 
##   left son=242 (39 obs) right son=243 (134 obs)
##   Primary splits:
##       age               < 82.5   to the right, improve=5.0010880, (0 missing)
##       reimbursement2008 < 6630   to the left,  improve=2.0288640, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.2040470, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.8841145, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8253101, (0 missing)
## 
## Node number 122: 69 observations
##   predicted class=B2  expected loss=0.3188406  P(node) =0.00345
##     class counts:    10    47     9     3     0
##    probabilities: 0.145 0.681 0.130 0.043 0.000 
## 
## Node number 123: 535 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5364486  P(node) =0.02675
##     class counts:   114   248   113    54     6
##    probabilities: 0.213 0.464 0.211 0.101 0.011 
##   left son=246 (282 obs) right son=247 (253 obs)
##   Primary splits:
##       depression   < 0.5    to the left,  improve=2.483857, (0 missing)
##       age          < 34     to the right, improve=2.414565, (0 missing)
##       alzheimers   < 0.5    to the left,  improve=1.680399, (0 missing)
##       osteoporosis < 0.5    to the left,  improve=1.549482, (0 missing)
##       ihd          < 0.5    to the left,  improve=1.112006, (0 missing)
##   Surrogate splits:
##       age               < 63.5   to the right, agree=0.574, adj=0.099, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.574, adj=0.099, (0 split)
##       reimbursement2008 < 8115   to the left,  agree=0.574, adj=0.099, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.568, adj=0.087, (0 split)
##       stroke            < 0.5    to the left,  agree=0.536, adj=0.020, (0 split)
## 
## Node number 124: 638 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.630094  P(node) =0.0319
##     class counts:   139   236   154    93    16
##    probabilities: 0.218 0.370 0.241 0.146 0.025 
##   left son=248 (612 obs) right son=249 (26 obs)
##   Primary splits:
##       age               < 44.5   to the right, improve=4.240890, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.955476, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.928245, (0 missing)
##       reimbursement2008 < 6575   to the right, improve=1.687162, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.121735, (0 missing)
## 
## Node number 125: 452 observations,    complexity param=0.0002028192
##   predicted class=B2  expected loss=0.4977876  P(node) =0.0226
##     class counts:    56   227   107    55     7
##    probabilities: 0.124 0.502 0.237 0.122 0.015 
##   left son=250 (143 obs) right son=251 (309 obs)
##   Primary splits:
##       reimbursement2008 < 5300   to the left,  improve=3.3421300, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.7850810, (0 missing)
##       age               < 39     to the left,  improve=1.2021390, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.9484846, (0 missing)
##       copd              < 0.5    to the left,  improve=0.7242827, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.715, adj=0.098, (0 split)
##       age        < 99.5   to the right, agree=0.686, adj=0.007, (0 split)
## 
## Node number 126: 53 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6603774  P(node) =0.00265
##     class counts:    16    18     4    14     1
##    probabilities: 0.302 0.340 0.075 0.264 0.019 
##   left son=252 (20 obs) right son=253 (33 obs)
##   Primary splits:
##       reimbursement2008 < 25800  to the right, improve=2.686221, (0 missing)
##       stroke            < 0.5    to the right, improve=1.745810, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.708468, (0 missing)
##       cancer            < 0.5    to the right, improve=1.513346, (0 missing)
##       copd              < 0.5    to the right, improve=1.510950, (0 missing)
##   Surrogate splits:
##       bucket2008    < 4.5    to the right, agree=0.679, adj=0.15, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.660, adj=0.10, (0 split)
## 
## Node number 127: 883 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6375991  P(node) =0.04415
##     class counts:   103   320   203   215    42
##    probabilities: 0.117 0.362 0.230 0.243 0.048 
##   left son=254 (396 obs) right son=255 (487 obs)
##   Primary splits:
##       reimbursement2008 < 26375  to the left,  improve=3.823201, (0 missing)
##       age               < 65.5   to the right, improve=2.689667, (0 missing)
##       copd              < 0.5    to the left,  improve=1.850928, (0 missing)
##       depression        < 0.5    to the left,  improve=1.564142, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=1.541530, (0 missing)
##   Surrogate splits:
##       bucket2008    < 3.5    to the left,  agree=0.736, adj=0.412, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.576, adj=0.056, (0 split)
##       copd          < 0.5    to the left,  agree=0.564, adj=0.028, (0 split)
## 
## Node number 160: 1586 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1431274  P(node) =0.0793
##     class counts:  1359   137    68    19     3
##    probabilities: 0.857 0.086 0.043 0.012 0.002 
##   left son=320 (756 obs) right son=321 (830 obs)
##   Primary splits:
##       age               < 71.5   to the left,  improve=0.9232109, (0 missing)
##       reimbursement2008 < 665    to the left,  improve=0.6940889, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6379602, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.5784235, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5106421, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 655    to the right, agree=0.530, adj=0.015, (0 split)
##       depression        < 0.5    to the right, agree=0.529, adj=0.012, (0 split)
##       copd              < 0.5    to the right, agree=0.528, adj=0.011, (0 split)
##       stroke            < 0.5    to the right, agree=0.524, adj=0.001, (0 split)
## 
## Node number 161: 178 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1966292  P(node) =0.0089
##     class counts:   143    25     7     3     0
##    probabilities: 0.803 0.140 0.039 0.017 0.000 
##   left son=322 (171 obs) right son=323 (7 obs)
##   Primary splits:
##       reimbursement2008 < 225    to the right, improve=2.3903390, (0 missing)
##       age               < 79.5   to the right, improve=0.6636044, (0 missing)
##       depression        < 0.5    to the right, improve=0.6166862, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.1555824, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.1467316, (0 missing)
## 
## Node number 170: 19 observations
##   predicted class=B1  expected loss=0.2631579  P(node) =0.00095
##     class counts:    14     2     1     2     0
##    probabilities: 0.737 0.105 0.053 0.105 0.000 
## 
## Node number 171: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     2     2     3     0     0
##    probabilities: 0.286 0.286 0.429 0.000 0.000 
## 
## Node number 176: 544 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1930147  P(node) =0.0272
##     class counts:   439    60    26    17     2
##    probabilities: 0.807 0.110 0.048 0.031 0.004 
##   left son=352 (338 obs) right son=353 (206 obs)
##   Primary splits:
##       reimbursement2008 < 905    to the left,  improve=1.0110110, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.9330888, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6888143, (0 missing)
##       age               < 83.5   to the left,  improve=0.6468196, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.4582147, (0 missing)
##   Surrogate splits:
##       age    < 97.5   to the left,  agree=0.629, adj=0.019, (0 split)
##       cancer < 0.5    to the left,  agree=0.627, adj=0.015, (0 split)
##       copd   < 0.5    to the left,  agree=0.623, adj=0.005, (0 split)
## 
## Node number 177: 267 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2397004  P(node) =0.01335
##     class counts:   203    45    12     7     0
##    probabilities: 0.760 0.169 0.045 0.026 0.000 
##   left son=354 (182 obs) right son=355 (85 obs)
##   Primary splits:
##       reimbursement2008 < 795    to the right, improve=1.3274960, (0 missing)
##       age               < 71.5   to the left,  improve=0.8090960, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6076067, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.4599499, (0 missing)
##       cancer            < 0.5    to the right, improve=0.4324521, (0 missing)
## 
## Node number 178: 133 observations
##   predicted class=B1  expected loss=0.2631579  P(node) =0.00665
##     class counts:    98    24     9     1     1
##    probabilities: 0.737 0.180 0.068 0.008 0.008 
## 
## Node number 179: 7 observations
##   predicted class=B2  expected loss=0.5714286  P(node) =0.00035
##     class counts:     2     3     1     1     0
##    probabilities: 0.286 0.429 0.143 0.143 0.000 
## 
## Node number 180: 586 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.2559727  P(node) =0.0293
##     class counts:   436    88    43    19     0
##    probabilities: 0.744 0.150 0.073 0.032 0.000 
##   left son=360 (449 obs) right son=361 (137 obs)
##   Primary splits:
##       age               < 67.5   to the right, improve=1.7267490, (0 missing)
##       copd              < 0.5    to the left,  improve=1.0095940, (0 missing)
##       reimbursement2008 < 1235   to the left,  improve=0.9296137, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.4946966, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.4469803, (0 missing)
## 
## Node number 181: 172 observations,    complexity param=0.0001303838
##   predicted class=B1  expected loss=0.3313953  P(node) =0.0086
##     class counts:   115    38    11     6     2
##    probabilities: 0.669 0.221 0.064 0.035 0.012 
##   left son=362 (143 obs) right son=363 (29 obs)
##   Primary splits:
##       age               < 83.5   to the left,  improve=1.8398370, (0 missing)
##       reimbursement2008 < 1115   to the right, improve=1.5955310, (0 missing)
##       copd              < 0.5    to the right, improve=1.1082360, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.0821000, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.9757667, (0 missing)
## 
## Node number 184: 691 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.2662808  P(node) =0.03455
##     class counts:   507   119    50    13     2
##    probabilities: 0.734 0.172 0.072 0.019 0.003 
##   left son=368 (628 obs) right son=369 (63 obs)
##   Primary splits:
##       reimbursement2008 < 1465   to the left,  improve=1.0827960, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8965233, (0 missing)
##       age               < 50     to the left,  improve=0.7515753, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.5491404, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.4331673, (0 missing)
## 
## Node number 185: 22 observations
##   predicted class=B1  expected loss=0.4545455  P(node) =0.0011
##     class counts:    12     6     1     1     2
##    probabilities: 0.545 0.273 0.045 0.045 0.091 
## 
## Node number 186: 15 observations
##   predicted class=B1  expected loss=0.1333333  P(node) =0.00075
##     class counts:    13     0     2     0     0
##    probabilities: 0.867 0.000 0.133 0.000 0.000 
## 
## Node number 187: 43 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5581395  P(node) =0.00215
##     class counts:    19    14     7     3     0
##    probabilities: 0.442 0.326 0.163 0.070 0.000 
##   left son=374 (35 obs) right son=375 (8 obs)
##   Primary splits:
##       reimbursement2008 < 1355   to the left,  improve=1.9905320, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.3960870, (0 missing)
##       age               < 78.5   to the left,  improve=0.5397797, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4476744, (0 missing)
##       depression        < 0.5    to the right, improve=0.3331424, (0 missing)
##   Surrogate splits:
##       arthritis < 0.5    to the left,  agree=0.837, adj=0.125, (0 split)
## 
## Node number 188: 90 observations
##   predicted class=B1  expected loss=0.2111111  P(node) =0.0045
##     class counts:    71    10     7     2     0
##    probabilities: 0.789 0.111 0.078 0.022 0.000 
## 
## Node number 189: 322 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3322981  P(node) =0.0161
##     class counts:   215    69    27    10     1
##    probabilities: 0.668 0.214 0.084 0.031 0.003 
##   left son=378 (310 obs) right son=379 (12 obs)
##   Primary splits:
##       age               < 46.5   to the right, improve=1.9484870, (0 missing)
##       reimbursement2008 < 1135   to the right, improve=1.2465950, (0 missing)
##       kidney            < 0.5    to the right, improve=0.8858863, (0 missing)
##       copd              < 0.5    to the right, improve=0.5966936, (0 missing)
##       depression        < 0.5    to the left,  improve=0.3370662, (0 missing)
## 
## Node number 190: 382 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4057592  P(node) =0.0191
##     class counts:   227    96    36    22     1
##    probabilities: 0.594 0.251 0.094 0.058 0.003 
##   left son=380 (352 obs) right son=381 (30 obs)
##   Primary splits:
##       reimbursement2008 < 1175   to the right, improve=1.447781, (0 missing)
##       arthritis         < 0.5    to the right, improve=1.260633, (0 missing)
##       depression        < 0.5    to the left,  improve=1.219881, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.175814, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.149973, (0 missing)
## 
## Node number 191: 25 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.56  P(node) =0.00125
##     class counts:     8    11     4     2     0
##    probabilities: 0.320 0.440 0.160 0.080 0.000 
##   left son=382 (7 obs) right son=383 (18 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=2.4349210, (0 missing)
##       age               < 94.5   to the left,  improve=1.3873020, (0 missing)
##       reimbursement2008 < 1490   to the right, improve=0.5936508, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.3138889, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1515   to the right, agree=0.84, adj=0.429, (0 split)
##       osteoporosis      < 0.5    to the right, agree=0.76, adj=0.143, (0 split)
## 
## Node number 192: 517 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3230174  P(node) =0.02585
##     class counts:   350   100    50    16     1
##    probabilities: 0.677 0.193 0.097 0.031 0.002 
##   left son=384 (395 obs) right son=385 (122 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=1.3507060, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.1170580, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9771406, (0 missing)
##       reimbursement2008 < 2555   to the right, improve=0.9492119, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.9266289, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1575   to the right, agree=0.766, adj=0.008, (0 split)
## 
## Node number 193: 7 observations
##   predicted class=B2  expected loss=0.5714286  P(node) =0.00035
##     class counts:     2     3     2     0     0
##    probabilities: 0.286 0.429 0.286 0.000 0.000 
## 
## Node number 194: 118 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.3389831  P(node) =0.0059
##     class counts:    78    31     6     2     1
##    probabilities: 0.661 0.263 0.051 0.017 0.008 
##   left son=388 (45 obs) right son=389 (73 obs)
##   Primary splits:
##       age               < 69.5   to the left,  improve=1.1850730, (0 missing)
##       reimbursement2008 < 3390   to the left,  improve=0.8082435, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4190278, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3093904, (0 missing)
##       cancer            < 0.5    to the right, improve=0.2861896, (0 missing)
##   Surrogate splits:
##       alzheimers < 0.5    to the right, agree=0.653, adj=0.089, (0 split)
##       stroke     < 0.5    to the right, agree=0.636, adj=0.044, (0 split)
## 
## Node number 195: 38 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5  P(node) =0.0019
##     class counts:    16    19     1     2     0
##    probabilities: 0.421 0.500 0.026 0.053 0.000 
##   left son=390 (12 obs) right son=391 (26 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=2.1828610, (0 missing)
##       age               < 82     to the right, improve=1.6698930, (0 missing)
##       reimbursement2008 < 2825   to the right, improve=0.6842105, (0 missing)
##       depression        < 0.5    to the right, improve=0.5608097, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5361943, (0 missing)
##   Surrogate splits:
##       age < 82     to the right, agree=0.763, adj=0.25, (0 split)
## 
## Node number 196: 32 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.0016
##     class counts:    24     4     4     0     0
##    probabilities: 0.750 0.125 0.125 0.000 0.000 
## 
## Node number 197: 78 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.4358974  P(node) =0.0039
##     class counts:    44    22     5     6     1
##    probabilities: 0.564 0.282 0.064 0.077 0.013 
##   left son=394 (20 obs) right son=395 (58 obs)
##   Primary splits:
##       reimbursement2008 < 2685   to the right, improve=1.5277630, (0 missing)
##       age               < 65     to the left,  improve=0.8171683, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7077891, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.4080586, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3333333, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the right, agree=0.846, adj=0.40, (0 split)
##       age        < 59.5   to the left,  agree=0.756, adj=0.05, (0 split)
## 
## Node number 198: 140 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5285714  P(node) =0.007
##     class counts:    66    43    27     3     1
##    probabilities: 0.471 0.307 0.193 0.021 0.007 
##   left son=396 (10 obs) right son=397 (130 obs)
##   Primary splits:
##       reimbursement2008 < 1775   to the left,  improve=1.7076920, (0 missing)
##       age               < 79.5   to the left,  improve=1.3659860, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.3345480, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.9142857, (0 missing)
##       cancer            < 0.5    to the right, improve=0.8461408, (0 missing)
## 
## Node number 199: 11 observations
##   predicted class=B2  expected loss=0.3636364  P(node) =0.00055
##     class counts:     3     7     1     0     0
##    probabilities: 0.273 0.636 0.091 0.000 0.000 
## 
## Node number 206: 10 observations
##   predicted class=B1  expected loss=0.4  P(node) =0.0005
##     class counts:     6     2     2     0     0
##    probabilities: 0.600 0.200 0.200 0.000 0.000 
## 
## Node number 207: 26 observations,    complexity param=0.000507048
##   predicted class=B3  expected loss=0.5769231  P(node) =0.0013
##     class counts:     3    10    11     2     0
##    probabilities: 0.115 0.385 0.423 0.077 0.000 
##   left son=414 (12 obs) right son=415 (14 obs)
##   Primary splits:
##       age               < 78.5   to the left,  improve=2.4047620, (0 missing)
##       depression        < 0.5    to the right, improve=1.7636360, (0 missing)
##       reimbursement2008 < 2405   to the left,  improve=1.4060150, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.0902260, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.4722222, (0 missing)
##   Surrogate splits:
##       arthritis         < 0.5    to the right, agree=0.692, adj=0.333, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.654, adj=0.250, (0 split)
##       cancer            < 0.5    to the right, agree=0.615, adj=0.167, (0 split)
##       diabetes          < 0.5    to the left,  agree=0.615, adj=0.167, (0 split)
##       reimbursement2008 < 2455   to the left,  agree=0.615, adj=0.167, (0 split)
## 
## Node number 208: 406 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.3990148  P(node) =0.0203
##     class counts:   244   105    35    19     3
##    probabilities: 0.601 0.259 0.086 0.047 0.007 
##   left son=416 (307 obs) right son=417 (99 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=1.7269200, (0 missing)
##       age               < 88.5   to the left,  improve=1.5011960, (0 missing)
##       reimbursement2008 < 2465   to the right, improve=1.4952500, (0 missing)
##       cancer            < 0.5    to the right, improve=1.0503980, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8595577, (0 missing)
## 
## Node number 209: 443 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.5146727  P(node) =0.02215
##     class counts:   215   141    57    26     4
##    probabilities: 0.485 0.318 0.129 0.059 0.009 
##   left son=418 (261 obs) right son=419 (182 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=4.055554, (0 missing)
##       diabetes          < 0.5    to the left,  improve=3.280522, (0 missing)
##       kidney            < 0.5    to the left,  improve=2.279095, (0 missing)
##       reimbursement2008 < 1775   to the left,  improve=2.187851, (0 missing)
##       copd              < 0.5    to the left,  improve=2.085109, (0 missing)
##   Surrogate splits:
##       kidney < 0.5    to the left,  agree=0.619, adj=0.071, (0 split)
##       copd   < 0.5    to the left,  agree=0.600, adj=0.027, (0 split)
##       age    < 38.5   to the right, agree=0.596, adj=0.016, (0 split)
## 
## Node number 210: 17 observations
##   predicted class=B2  expected loss=0.4705882  P(node) =0.00085
##     class counts:     4     9     4     0     0
##    probabilities: 0.235 0.529 0.235 0.000 0.000 
## 
## Node number 211: 14 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.0007
##     class counts:     5     2     6     1     0
##    probabilities: 0.357 0.143 0.429 0.071 0.000 
## 
## Node number 212: 55 observations
##   predicted class=B1  expected loss=0.3272727  P(node) =0.00275
##     class counts:    37    12     3     3     0
##    probabilities: 0.673 0.218 0.055 0.055 0.000 
## 
## Node number 213: 25 observations,    complexity param=0.000380286
##   predicted class=B2  expected loss=0.56  P(node) =0.00125
##     class counts:     9    11     2     3     0
##    probabilities: 0.360 0.440 0.080 0.120 0.000 
##   left son=426 (15 obs) right son=427 (10 obs)
##   Primary splits:
##       age               < 97.5   to the right, improve=1.6666670, (0 missing)
##       reimbursement2008 < 1995   to the right, improve=0.5153846, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1179487, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.1179487, (0 missing)
##       kidney            < 0.5    to the right, improve=0.1142857, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1685   to the right, agree=0.68, adj=0.2, (0 split)
## 
## Node number 214: 298 observations,    complexity param=0.001064801
##   predicted class=B1  expected loss=0.590604  P(node) =0.0149
##     class counts:   122   117    43    15     1
##    probabilities: 0.409 0.393 0.144 0.050 0.003 
##   left son=428 (162 obs) right son=429 (136 obs)
##   Primary splits:
##       age               < 71.5   to the left,  improve=3.1447400, (0 missing)
##       reimbursement2008 < 1760   to the left,  improve=2.8458740, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9979622, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7325015, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.4523398, (0 missing)
##   Surrogate splits:
##       stroke            < 0.5    to the left,  agree=0.550, adj=0.015, (0 split)
##       reimbursement2008 < 2495   to the left,  agree=0.550, adj=0.015, (0 split)
##       diabetes          < 0.5    to the right, agree=0.547, adj=0.007, (0 split)
## 
## Node number 215: 17 observations
##   predicted class=B2  expected loss=0.2941176  P(node) =0.00085
##     class counts:     2    12     2     1     0
##    probabilities: 0.118 0.706 0.118 0.059 0.000 
## 
## Node number 216: 281 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.4519573  P(node) =0.01405
##     class counts:   154    78    35    12     2
##    probabilities: 0.548 0.278 0.125 0.043 0.007 
##   left son=432 (68 obs) right son=433 (213 obs)
##   Primary splits:
##       age               < 67.5   to the left,  improve=1.4795500, (0 missing)
##       reimbursement2008 < 2995   to the right, improve=1.3998900, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.3998900, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.8817733, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6232495, (0 missing)
## 
## Node number 217: 36 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.3888889  P(node) =0.0018
##     class counts:     8    22     6     0     0
##    probabilities: 0.222 0.611 0.167 0.000 0.000 
##   left son=434 (10 obs) right son=435 (26 obs)
##   Primary splits:
##       reimbursement2008 < 2770   to the left,  improve=2.4239320, (0 missing)
##       age               < 77.5   to the left,  improve=1.1944440, (0 missing)
##       depression        < 0.5    to the left,  improve=1.0277780, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.9725830, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.9470085, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.778, adj=0.2, (0 split)
##       age        < 62.5   to the left,  agree=0.750, adj=0.1, (0 split)
## 
## Node number 218: 213 observations,    complexity param=0.000760572
##   predicted class=B1  expected loss=0.6103286  P(node) =0.01065
##     class counts:    83    75    33    22     0
##    probabilities: 0.390 0.352 0.155 0.103 0.000 
##   left son=436 (146 obs) right son=437 (67 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=2.4874440, (0 missing)
##       reimbursement2008 < 3335   to the right, improve=1.9134220, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.5529040, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.9344707, (0 missing)
##       copd              < 0.5    to the left,  improve=0.7994731, (0 missing)
##   Surrogate splits:
##       age < 35     to the right, agree=0.69, adj=0.015, (0 split)
## 
## Node number 219: 84 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.5119048  P(node) =0.0042
##     class counts:    20    41    20     3     0
##    probabilities: 0.238 0.488 0.238 0.036 0.000 
##   left son=438 (57 obs) right son=439 (27 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=1.5891120, (0 missing)
##       reimbursement2008 < 2735   to the right, improve=1.5503000, (0 missing)
##       age               < 70.5   to the right, improve=0.6885269, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.6357352, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4006211, (0 missing)
##   Surrogate splits:
##       age               < 91.5   to the left,  agree=0.726, adj=0.148, (0 split)
##       reimbursement2008 < 3415   to the left,  agree=0.702, adj=0.074, (0 split)
##       diabetes          < 0.5    to the right, agree=0.690, adj=0.037, (0 split)
## 
## Node number 220: 157 observations,    complexity param=0.0002788764
##   predicted class=B2  expected loss=0.5350318  P(node) =0.00785
##     class counts:    50    73    28     5     1
##    probabilities: 0.318 0.465 0.178 0.032 0.006 
##   left son=440 (150 obs) right son=441 (7 obs)
##   Primary splits:
##       stroke            < 0.5    to the left,  improve=1.886903, (0 missing)
##       copd              < 0.5    to the left,  improve=1.391085, (0 missing)
##       age               < 89.5   to the left,  improve=1.341972, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.236864, (0 missing)
##       reimbursement2008 < 2575   to the right, improve=1.066105, (0 missing)
## 
## Node number 221: 17 observations
##   predicted class=B3  expected loss=0.5294118  P(node) =0.00085
##     class counts:     4     4     8     1     0
##    probabilities: 0.235 0.235 0.471 0.059 0.000 
## 
## Node number 222: 81 observations,    complexity param=0.000190143
##   predicted class=B2  expected loss=0.4691358  P(node) =0.00405
##     class counts:    23    43     8     6     1
##    probabilities: 0.284 0.531 0.099 0.074 0.012 
##   left son=444 (70 obs) right son=445 (11 obs)
##   Primary splits:
##       reimbursement2008 < 3075   to the right, improve=1.2392180, (0 missing)
##       copd              < 0.5    to the left,  improve=1.1799880, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.9098037, (0 missing)
##       age               < 88.5   to the right, improve=0.6730540, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.3344166, (0 missing)
## 
## Node number 223: 31 observations
##   predicted class=B2  expected loss=0.1935484  P(node) =0.00155
##     class counts:     2    25     2     2     0
##    probabilities: 0.065 0.806 0.065 0.065 0.000 
## 
## Node number 224: 330 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.3787879  P(node) =0.0165
##     class counts:   205    77    36    10     2
##    probabilities: 0.621 0.233 0.109 0.030 0.006 
##   left son=448 (120 obs) right son=449 (210 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=3.020996, (0 missing)
##       reimbursement2008 < 7060   to the right, improve=2.104329, (0 missing)
##       age               < 59.5   to the right, improve=1.322458, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.319301, (0 missing)
##       copd              < 0.5    to the left,  improve=1.189474, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4060   to the left,  agree=0.652, adj=0.042, (0 split)
##       age               < 33.5   to the left,  agree=0.645, adj=0.025, (0 split)
## 
## Node number 225: 89 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.494382  P(node) =0.00445
##     class counts:    45    34     6     3     1
##    probabilities: 0.506 0.382 0.067 0.034 0.011 
##   left son=450 (15 obs) right son=451 (74 obs)
##   Primary splits:
##       reimbursement2008 < 12275  to the right, improve=3.3794110, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.9367485, (0 missing)
##       age               < 84.5   to the left,  improve=0.9235279, (0 missing)
##       ihd               < 0.5    to the right, improve=0.5528036, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5281343, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.921, adj=0.533, (0 split)
## 
## Node number 226: 58 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.4655172  P(node) =0.0029
##     class counts:    31    15     8     4     0
##    probabilities: 0.534 0.259 0.138 0.069 0.000 
##   left son=452 (27 obs) right son=453 (31 obs)
##   Primary splits:
##       reimbursement2008 < 6600   to the right, improve=2.6670370, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.9714330, (0 missing)
##       age               < 52.5   to the right, improve=1.1824140, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.9855451, (0 missing)
##       copd              < 0.5    to the right, improve=0.6557471, (0 missing)
##   Surrogate splits:
##       bucket2008    < 2.5    to the right, agree=0.948, adj=0.889, (0 split)
##       alzheimers    < 0.5    to the right, agree=0.655, adj=0.259, (0 split)
##       copd          < 0.5    to the right, agree=0.603, adj=0.148, (0 split)
##       heart.failure < 0.5    to the right, agree=0.603, adj=0.148, (0 split)
##       age           < 59     to the right, agree=0.586, adj=0.111, (0 split)
## 
## Node number 227: 86 observations,    complexity param=0.0003549336
##   predicted class=B2  expected loss=0.627907  P(node) =0.0043
##     class counts:    30    32    21     3     0
##    probabilities: 0.349 0.372 0.244 0.035 0.000 
##   left son=454 (14 obs) right son=455 (72 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=1.4390000, (0 missing)
##       copd              < 0.5    to the right, improve=1.2671440, (0 missing)
##       age               < 81.5   to the right, improve=1.2282230, (0 missing)
##       reimbursement2008 < 4375   to the left,  improve=0.9141660, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.6448968, (0 missing)
## 
## Node number 228: 42 observations,    complexity param=0.000760572
##   predicted class=B1  expected loss=0.5714286  P(node) =0.0021
##     class counts:    18    15     4     5     0
##    probabilities: 0.429 0.357 0.095 0.119 0.000 
##   left son=456 (10 obs) right son=457 (32 obs)
##   Primary splits:
##       reimbursement2008 < 3950   to the left,  improve=2.4148810, (0 missing)
##       copd              < 0.5    to the left,  improve=1.5594190, (0 missing)
##       age               < 64.5   to the left,  improve=1.4964990, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.1023810, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7069264, (0 missing)
## 
## Node number 229: 13 observations
##   predicted class=B3  expected loss=0.3846154  P(node) =0.00065
##     class counts:     3     0     8     2     0
##    probabilities: 0.231 0.000 0.615 0.154 0.000 
## 
## Node number 230: 41 observations
##   predicted class=B2  expected loss=0.4390244  P(node) =0.00205
##     class counts:     9    23     5     4     0
##    probabilities: 0.220 0.561 0.122 0.098 0.000 
## 
## Node number 231: 23 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.6086957  P(node) =0.00115
##     class counts:     6     6     9     2     0
##    probabilities: 0.261 0.261 0.391 0.087 0.000 
##   left son=462 (12 obs) right son=463 (11 obs)
##   Primary splits:
##       reimbursement2008 < 9740   to the right, improve=1.4920950, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.0489130, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.9011858, (0 missing)
##       age               < 82.5   to the right, improve=0.4774845, (0 missing)
##       kidney            < 0.5    to the right, improve=0.2572464, (0 missing)
##   Surrogate splits:
##       age        < 73.5   to the left,  agree=0.783, adj=0.545, (0 split)
##       bucket2008 < 2.5    to the right, agree=0.783, adj=0.545, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.652, adj=0.273, (0 split)
##       arthritis  < 0.5    to the left,  agree=0.652, adj=0.273, (0 split)
##       stroke     < 0.5    to the right, agree=0.565, adj=0.091, (0 split)
## 
## Node number 234: 136 observations,    complexity param=0.0006084576
##   predicted class=B2  expected loss=0.5147059  P(node) =0.0068
##     class counts:    40    66    23     7     0
##    probabilities: 0.294 0.485 0.169 0.051 0.000 
##   left son=468 (72 obs) right son=469 (64 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=2.205882, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=2.001349, (0 missing)
##       reimbursement2008 < 3710   to the left,  improve=1.407495, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.335690, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.307073, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 7755   to the left,  agree=0.574, adj=0.094, (0 split)
##       arthritis         < 0.5    to the right, agree=0.566, adj=0.078, (0 split)
##       bucket2008        < 3.5    to the left,  agree=0.559, adj=0.063, (0 split)
##       age               < 70.5   to the left,  agree=0.551, adj=0.047, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.551, adj=0.047, (0 split)
## 
## Node number 235: 57 observations,    complexity param=0.0006084576
##   predicted class=B1  expected loss=0.5789474  P(node) =0.00285
##     class counts:    24    15    13     5     0
##    probabilities: 0.421 0.263 0.228 0.088 0.000 
##   left son=470 (46 obs) right son=471 (11 obs)
##   Primary splits:
##       cancer            < 0.5    to the left,  improve=1.998405, (0 missing)
##       reimbursement2008 < 7955   to the right, improve=1.956558, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.956558, (0 missing)
##       age               < 91.5   to the right, improve=1.915288, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.477193, (0 missing)
## 
## Node number 238: 8 observations
##   predicted class=B2  expected loss=0.125  P(node) =0.0004
##     class counts:     0     7     0     1     0
##    probabilities: 0.000 0.875 0.000 0.125 0.000 
## 
## Node number 239: 86 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.5813953  P(node) =0.0043
##     class counts:    18    36    24     8     0
##    probabilities: 0.209 0.419 0.279 0.093 0.000 
##   left son=478 (79 obs) right son=479 (7 obs)
##   Primary splits:
##       reimbursement2008 < 15470  to the left,  improve=1.3701160, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.1865130, (0 missing)
##       age               < 75.5   to the left,  improve=0.7490688, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7421039, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.6663848, (0 missing)
## 
## Node number 240: 277 observations,    complexity param=0.0008746577
##   predicted class=B1  expected loss=0.5884477  P(node) =0.01385
##     class counts:   114    91    52    19     1
##    probabilities: 0.412 0.329 0.188 0.069 0.004 
##   left son=480 (199 obs) right son=481 (78 obs)
##   Primary splits:
##       reimbursement2008 < 8845   to the left,  improve=3.810926, (0 missing)
##       copd              < 0.5    to the left,  improve=3.392896, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=2.186722, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.961790, (0 missing)
##       age               < 65.5   to the right, improve=1.441728, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.953, adj=0.833, (0 split)
##       age        < 29.5   to the right, agree=0.722, adj=0.013, (0 split)
## 
## Node number 241: 514 observations,    complexity param=0.0008746577
##   predicted class=B2  expected loss=0.5583658  P(node) =0.0257
##     class counts:   178   227    77    29     3
##    probabilities: 0.346 0.442 0.150 0.056 0.006 
##   left son=482 (327 obs) right son=483 (187 obs)
##   Primary splits:
##       reimbursement2008 < 5045   to the right, improve=4.8841090, (0 missing)
##       age               < 77.5   to the left,  improve=3.3027050, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.9008760, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.9763248, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7270267, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.722, adj=0.235, (0 split)
## 
## Node number 242: 39 observations
##   predicted class=B2  expected loss=0.3076923  P(node) =0.00195
##     class counts:     4    27     6     1     1
##    probabilities: 0.103 0.692 0.154 0.026 0.026 
## 
## Node number 243: 134 observations,    complexity param=0.0005324004
##   predicted class=B2  expected loss=0.641791  P(node) =0.0067
##     class counts:    28    48    47    11     0
##    probabilities: 0.209 0.358 0.351 0.082 0.000 
##   left son=486 (120 obs) right son=487 (14 obs)
##   Primary splits:
##       age               < 55     to the right, improve=2.1647830, (0 missing)
##       reimbursement2008 < 6810   to the left,  improve=1.9339560, (0 missing)
##       depression        < 0.5    to the left,  improve=1.6866340, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.1492540, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.6824682, (0 missing)
## 
## Node number 246: 282 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5283688  P(node) =0.0141
##     class counts:    68   133    44    33     4
##    probabilities: 0.241 0.472 0.156 0.117 0.014 
##   left son=492 (183 obs) right son=493 (99 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=1.953103, (0 missing)
##       age               < 79.5   to the right, improve=1.706579, (0 missing)
##       copd              < 0.5    to the left,  improve=1.416467, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.155080, (0 missing)
##       reimbursement2008 < 3985   to the left,  improve=1.070900, (0 missing)
## 
## Node number 247: 253 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5454545  P(node) =0.01265
##     class counts:    46   115    69    21     2
##    probabilities: 0.182 0.455 0.273 0.083 0.008 
##   left son=494 (241 obs) right son=495 (12 obs)
##   Primary splits:
##       age               < 40.5   to the right, improve=1.7374600, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.3259550, (0 missing)
##       reimbursement2008 < 27370  to the left,  improve=1.2197450, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.9664812, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8621215, (0 missing)
## 
## Node number 248: 612 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.625817  P(node) =0.0306
##     class counts:   138   229   139    90    16
##    probabilities: 0.225 0.374 0.227 0.147 0.026 
##   left son=496 (346 obs) right son=497 (266 obs)
##   Primary splits:
##       reimbursement2008 < 6575   to the right, improve=1.895835, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.891624, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.621569, (0 missing)
##       age               < 79.5   to the right, improve=1.437351, (0 missing)
##       depression        < 0.5    to the left,  improve=1.158424, (0 missing)
##   Surrogate splits:
##       bucket2008    < 2.5    to the right, agree=0.884, adj=0.733, (0 split)
##       heart.failure < 0.5    to the right, agree=0.592, adj=0.060, (0 split)
##       ihd           < 0.5    to the right, agree=0.585, adj=0.045, (0 split)
##       age           < 97.5   to the left,  agree=0.574, adj=0.019, (0 split)
## 
## Node number 249: 26 observations,    complexity param=0.0001521144
##   predicted class=B3  expected loss=0.4230769  P(node) =0.0013
##     class counts:     1     7    15     3     0
##    probabilities: 0.038 0.269 0.577 0.115 0.000 
##   left son=498 (7 obs) right son=499 (19 obs)
##   Primary splits:
##       age               < 34     to the left,  improve=1.2272990, (0 missing)
##       reimbursement2008 < 9145   to the left,  improve=0.7893414, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.6847662, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.4615385, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.3738928, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 12030  to the right, agree=0.808, adj=0.286, (0 split)
## 
## Node number 250: 143 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.4055944  P(node) =0.00715
##     class counts:    20    85    22    15     1
##    probabilities: 0.140 0.594 0.154 0.105 0.007 
##   left son=500 (11 obs) right son=501 (132 obs)
##   Primary splits:
##       reimbursement2008 < 5155   to the right, improve=1.6981350, (0 missing)
##       age               < 81.5   to the right, improve=1.1198620, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.6517483, (0 missing)
##       cancer            < 0.5    to the right, improve=0.5239179, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5030303, (0 missing)
## 
## Node number 251: 309 observations,    complexity param=0.0002028192
##   predicted class=B2  expected loss=0.5404531  P(node) =0.01545
##     class counts:    36   142    85    40     6
##    probabilities: 0.117 0.460 0.275 0.129 0.019 
##   left son=502 (24 obs) right son=503 (285 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=1.6851900, (0 missing)
##       age               < 95.5   to the right, improve=1.5390930, (0 missing)
##       depression        < 0.5    to the right, improve=0.9172647, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8659759, (0 missing)
##       reimbursement2008 < 5385   to the right, improve=0.7334569, (0 missing)
## 
## Node number 252: 20 observations,    complexity param=0.0004563432
##   predicted class=B1  expected loss=0.45  P(node) =0.001
##     class counts:    11     5     1     3     0
##    probabilities: 0.550 0.250 0.050 0.150 0.000 
##   left son=504 (11 obs) right son=505 (9 obs)
##   Primary splits:
##       age               < 79.5   to the left,  improve=3.4121210, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.1890110, (0 missing)
##       reimbursement2008 < 40870  to the left,  improve=0.3978022, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1166667, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 41445  to the left,  agree=0.65, adj=0.222, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.60, adj=0.111, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.60, adj=0.111, (0 split)
## 
## Node number 253: 33 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6060606  P(node) =0.00165
##     class counts:     5    13     3    11     1
##    probabilities: 0.152 0.394 0.091 0.333 0.030 
##   left son=506 (20 obs) right son=507 (13 obs)
##   Primary splits:
##       age               < 79.5   to the left,  improve=3.605361, (0 missing)
##       arthritis         < 0.5    to the right, improve=2.541515, (0 missing)
##       cancer            < 0.5    to the right, improve=1.984848, (0 missing)
##       copd              < 0.5    to the right, improve=1.773737, (0 missing)
##       reimbursement2008 < 22825  to the left,  improve=1.341515, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 17295  to the right, agree=0.727, adj=0.308, (0 split)
##       bucket2008        < 3.5    to the right, agree=0.667, adj=0.154, (0 split)
##       heart.failure     < 0.5    to the right, agree=0.636, adj=0.077, (0 split)
## 
## Node number 254: 396 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6590909  P(node) =0.0198
##     class counts:    66   135    99    79    17
##    probabilities: 0.167 0.341 0.250 0.199 0.043 
##   left son=508 (233 obs) right son=509 (163 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=2.997912, (0 missing)
##       copd              < 0.5    to the left,  improve=1.877365, (0 missing)
##       age               < 49.5   to the right, improve=1.867161, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.727362, (0 missing)
##       reimbursement2008 < 23350  to the right, improve=1.426471, (0 missing)
##   Surrogate splits:
##       age               < 79.5   to the left,  agree=0.593, adj=0.012, (0 split)
##       reimbursement2008 < 15370  to the right, agree=0.593, adj=0.012, (0 split)
## 
## Node number 255: 487 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6201232  P(node) =0.02435
##     class counts:    37   185   104   136    25
##    probabilities: 0.076 0.380 0.214 0.279 0.051 
##   left son=510 (65 obs) right son=511 (422 obs)
##   Primary splits:
##       age               < 88.5   to the right, improve=4.7932710, (0 missing)
##       reimbursement2008 < 32590  to the left,  improve=2.4336710, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.5095490, (0 missing)
##       stroke            < 0.5    to the right, improve=1.4520590, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9634536, (0 missing)
## 
## Node number 320: 756 observations
##   predicted class=B1  expected loss=0.1216931  P(node) =0.0378
##     class counts:   664    57    27     7     1
##    probabilities: 0.878 0.075 0.036 0.009 0.001 
## 
## Node number 321: 830 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1626506  P(node) =0.0415
##     class counts:   695    80    41    12     2
##    probabilities: 0.837 0.096 0.049 0.014 0.002 
##   left son=642 (801 obs) right son=643 (29 obs)
##   Primary splits:
##       reimbursement2008 < 665    to the left,  improve=1.0300310, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4238073, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.4152878, (0 missing)
##       age               < 83.5   to the right, improve=0.3253936, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3055330, (0 missing)
## 
## Node number 322: 171 observations
##   predicted class=B1  expected loss=0.1812865  P(node) =0.00855
##     class counts:   140    21     7     3     0
##    probabilities: 0.819 0.123 0.041 0.018 0.000 
## 
## Node number 323: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     3     4     0     0     0
##    probabilities: 0.429 0.571 0.000 0.000 0.000 
## 
## Node number 352: 338 observations
##   predicted class=B1  expected loss=0.1745562  P(node) =0.0169
##     class counts:   279    29    20     8     2
##    probabilities: 0.825 0.086 0.059 0.024 0.006 
## 
## Node number 353: 206 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.223301  P(node) =0.0103
##     class counts:   160    31     6     9     0
##    probabilities: 0.777 0.150 0.029 0.044 0.000 
##   left son=706 (149 obs) right son=707 (57 obs)
##   Primary splits:
##       reimbursement2008 < 955    to the right, improve=2.3303040, (0 missing)
##       age               < 83.5   to the left,  improve=1.0927070, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.2820581, (0 missing)
##       depression        < 0.5    to the left,  improve=0.2779032, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2242064, (0 missing)
## 
## Node number 354: 182 observations
##   predicted class=B1  expected loss=0.2087912  P(node) =0.0091
##     class counts:   144    24     9     5     0
##    probabilities: 0.791 0.132 0.049 0.027 0.000 
## 
## Node number 355: 85 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3058824  P(node) =0.00425
##     class counts:    59    21     3     2     0
##    probabilities: 0.694 0.247 0.035 0.024 0.000 
##   left son=710 (76 obs) right son=711 (9 obs)
##   Primary splits:
##       reimbursement2008 < 785    to the left,  improve=1.6035430, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.6444788, (0 missing)
##       age               < 67.5   to the left,  improve=0.4285599, (0 missing)
##       kidney            < 0.5    to the right, improve=0.2709929, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2638534, (0 missing)
## 
## Node number 360: 449 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.2383073  P(node) =0.02245
##     class counts:   342    57    36    14     0
##    probabilities: 0.762 0.127 0.080 0.031 0.000 
##   left son=720 (283 obs) right son=721 (166 obs)
##   Primary splits:
##       reimbursement2008 < 1335   to the left,  improve=0.9925853, (0 missing)
##       age               < 86.5   to the right, improve=0.7150894, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.4184894, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.3114171, (0 missing)
##       copd              < 0.5    to the left,  improve=0.2866033, (0 missing)
##   Surrogate splits:
##       arthritis < 0.5    to the left,  agree=0.639, adj=0.024, (0 split)
##       cancer    < 0.5    to the left,  agree=0.635, adj=0.012, (0 split)
## 
## Node number 361: 137 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.3138686  P(node) =0.00685
##     class counts:    94    31     7     5     0
##    probabilities: 0.686 0.226 0.051 0.036 0.000 
##   left son=722 (50 obs) right son=723 (87 obs)
##   Primary splits:
##       reimbursement2008 < 1345   to the right, improve=0.88131890, (0 missing)
##       age               < 66.5   to the right, improve=0.69730870, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.63774780, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.09490691, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.05691905, (0 missing)
## 
## Node number 362: 143 observations,    complexity param=0.0001303838
##   predicted class=B1  expected loss=0.2937063  P(node) =0.00715
##     class counts:   101    28     8     4     2
##    probabilities: 0.706 0.196 0.056 0.028 0.014 
##   left son=724 (44 obs) right son=725 (99 obs)
##   Primary splits:
##       age               < 75.5   to the right, improve=1.3014760, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.1065060, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6625760, (0 missing)
##       reimbursement2008 < 1105   to the right, improve=0.6192812, (0 missing)
##       copd              < 0.5    to the right, improve=0.5462853, (0 missing)
## 
## Node number 363: 29 observations,    complexity param=0.0001303838
##   predicted class=B1  expected loss=0.5172414  P(node) =0.00145
##     class counts:    14    10     3     2     0
##    probabilities: 0.483 0.345 0.103 0.069 0.000 
##   left son=726 (17 obs) right son=727 (12 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=1.687965, (0 missing)
##       depression        < 0.5    to the right, improve=1.400383, (0 missing)
##       reimbursement2008 < 1230   to the right, improve=1.163009, (0 missing)
##       age               < 89.5   to the right, improve=1.116256, (0 missing)
##   Surrogate splits:
##       depression        < 0.5    to the left,  agree=0.690, adj=0.250, (0 split)
##       age               < 88     to the right, agree=0.655, adj=0.167, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.655, adj=0.167, (0 split)
##       arthritis         < 0.5    to the left,  agree=0.621, adj=0.083, (0 split)
##       reimbursement2008 < 1315   to the left,  agree=0.621, adj=0.083, (0 split)
## 
## Node number 368: 628 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.2563694  P(node) =0.0314
##     class counts:   467   104    43    12     2
##    probabilities: 0.744 0.166 0.068 0.019 0.003 
##   left son=736 (455 obs) right son=737 (173 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=1.5481310, (0 missing)
##       age               < 50     to the left,  improve=1.0731200, (0 missing)
##       reimbursement2008 < 1415   to the right, improve=0.7768717, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.6957436, (0 missing)
##       copd              < 0.5    to the right, improve=0.4845812, (0 missing)
##   Surrogate splits:
##       stroke < 0.5    to the left,  agree=0.726, adj=0.006, (0 split)
## 
## Node number 369: 63 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3650794  P(node) =0.00315
##     class counts:    40    15     7     1     0
##    probabilities: 0.635 0.238 0.111 0.016 0.000 
##   left son=738 (52 obs) right son=739 (11 obs)
##   Primary splits:
##       reimbursement2008 < 1485   to the right, improve=1.6751580, (0 missing)
##       age               < 77     to the left,  improve=1.2620310, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.8989344, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.8365607, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.4831933, (0 missing)
## 
## Node number 374: 35 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4857143  P(node) =0.00175
##     class counts:    18     9     5     3     0
##    probabilities: 0.514 0.257 0.143 0.086 0.000 
##   left son=748 (28 obs) right son=749 (7 obs)
##   Primary splits:
##       reimbursement2008 < 895    to the right, improve=1.2428570, (0 missing)
##       age               < 78.5   to the left,  improve=0.5571429, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1771429, (0 missing)
##       depression        < 0.5    to the right, improve=0.1771429, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.1695612, (0 missing)
##   Surrogate splits:
##       arthritis < 0.5    to the left,  agree=0.829, adj=0.143, (0 split)
## 
## Node number 375: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     1     5     2     0     0
##    probabilities: 0.125 0.625 0.250 0.000 0.000 
## 
## Node number 378: 310 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3193548  P(node) =0.0155
##     class counts:   211    65    24     9     1
##    probabilities: 0.681 0.210 0.077 0.029 0.003 
##   left son=756 (213 obs) right son=757 (97 obs)
##   Primary splits:
##       reimbursement2008 < 835    to the right, improve=1.2234200, (0 missing)
##       kidney            < 0.5    to the right, improve=0.9543067, (0 missing)
##       age               < 94.5   to the left,  improve=0.6199997, (0 missing)
##       copd              < 0.5    to the right, improve=0.5598660, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.3296654, (0 missing)
## 
## Node number 379: 12 observations
##   predicted class=B1  expected loss=0.6666667  P(node) =0.0006
##     class counts:     4     4     3     1     0
##    probabilities: 0.333 0.333 0.250 0.083 0.000 
## 
## Node number 380: 352 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4005682  P(node) =0.0176
##     class counts:   211    93    30    18     0
##    probabilities: 0.599 0.264 0.085 0.051 0.000 
##   left son=760 (242 obs) right son=761 (110 obs)
##   Primary splits:
##       depression    < 0.5    to the left,  improve=1.422004, (0 missing)
##       alzheimers    < 0.5    to the left,  improve=1.222427, (0 missing)
##       heart.failure < 0.5    to the left,  improve=1.193813, (0 missing)
##       kidney        < 0.5    to the left,  improve=1.141542, (0 missing)
##       age           < 41.5   to the left,  improve=1.015276, (0 missing)
##   Surrogate splits:
##       age < 31.5   to the right, agree=0.69, adj=0.009, (0 split)
## 
## Node number 381: 30 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4666667  P(node) =0.0015
##     class counts:    16     3     6     4     1
##    probabilities: 0.533 0.100 0.200 0.133 0.033 
##   left son=762 (22 obs) right son=763 (8 obs)
##   Primary splits:
##       age               < 70     to the right, improve=1.5590910, (0 missing)
##       reimbursement2008 < 1165   to the right, improve=0.3186603, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3000000, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.2421053, (0 missing)
##       depression        < 0.5    to the right, improve=0.1000000, (0 missing)
## 
## Node number 382: 7 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.00035
##     class counts:     5     1     1     0     0
##    probabilities: 0.714 0.143 0.143 0.000 0.000 
## 
## Node number 383: 18 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.0009
##     class counts:     3    10     3     2     0
##    probabilities: 0.167 0.556 0.167 0.111 0.000 
## 
## Node number 384: 395 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3012658  P(node) =0.01975
##     class counts:   276    70    39     9     1
##    probabilities: 0.699 0.177 0.099 0.023 0.003 
##   left son=768 (288 obs) right son=769 (107 obs)
##   Primary splits:
##       age               < 68.5   to the right, improve=1.6366860, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.9039390, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7765844, (0 missing)
##       reimbursement2008 < 2155   to the left,  improve=0.6564463, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5270843, (0 missing)
## 
## Node number 385: 122 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3934426  P(node) =0.0061
##     class counts:    74    30    11     7     0
##    probabilities: 0.607 0.246 0.090 0.057 0.000 
##   left son=770 (22 obs) right son=771 (100 obs)
##   Primary splits:
##       age               < 64     to the left,  improve=3.407899, (0 missing)
##       copd              < 0.5    to the left,  improve=2.182772, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.651095, (0 missing)
##       arthritis         < 0.5    to the right, improve=1.570224, (0 missing)
##       reimbursement2008 < 1715   to the left,  improve=1.522952, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2575   to the right, agree=0.828, adj=0.045, (0 split)
## 
## Node number 388: 45 observations
##   predicted class=B1  expected loss=0.2444444  P(node) =0.00225
##     class counts:    34     8     2     1     0
##    probabilities: 0.756 0.178 0.044 0.022 0.000 
## 
## Node number 389: 73 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.3972603  P(node) =0.00365
##     class counts:    44    23     4     1     1
##    probabilities: 0.603 0.315 0.055 0.014 0.014 
##   left son=778 (66 obs) right son=779 (7 obs)
##   Primary splits:
##       reimbursement2008 < 3390   to the left,  improve=1.0555650, (0 missing)
##       age               < 73.5   to the right, improve=0.9205119, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3975568, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.3383422, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.3014529, (0 missing)
## 
## Node number 390: 12 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0006
##     class counts:     8     3     0     1     0
##    probabilities: 0.667 0.250 0.000 0.083 0.000 
## 
## Node number 391: 26 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.3846154  P(node) =0.0013
##     class counts:     8    16     1     1     0
##    probabilities: 0.308 0.615 0.038 0.038 0.000 
##   left son=782 (7 obs) right son=783 (19 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=1.0289180, (0 missing)
##       age               < 71.5   to the left,  improve=0.9850816, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7134238, (0 missing)
##       reimbursement2008 < 2715   to the right, improve=0.6578089, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1266628, (0 missing)
##   Surrogate splits:
##       age < 83     to the right, agree=0.769, adj=0.143, (0 split)
## 
## Node number 394: 20 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.001
##     class counts:    15     3     0     2     0
##    probabilities: 0.750 0.150 0.000 0.100 0.000 
## 
## Node number 395: 58 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.5  P(node) =0.0029
##     class counts:    29    19     5     4     1
##    probabilities: 0.500 0.328 0.086 0.069 0.017 
##   left son=790 (50 obs) right son=791 (8 obs)
##   Primary splits:
##       reimbursement2008 < 2425   to the left,  improve=1.4217240, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.3465590, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.9017241, (0 missing)
##       age               < 71.5   to the right, improve=0.8647468, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.6097512, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.879, adj=0.125, (0 split)
## 
## Node number 396: 10 observations
##   predicted class=B1  expected loss=0.3  P(node) =0.0005
##     class counts:     7     0     3     0     0
##    probabilities: 0.700 0.000 0.300 0.000 0.000 
## 
## Node number 397: 130 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5461538  P(node) =0.0065
##     class counts:    59    43    24     3     1
##    probabilities: 0.454 0.331 0.185 0.023 0.008 
##   left son=794 (9 obs) right son=795 (121 obs)
##   Primary splits:
##       reimbursement2008 < 3265   to the right, improve=1.5391400, (0 missing)
##       age               < 79.5   to the left,  improve=1.1170220, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.0842510, (0 missing)
##       arthritis         < 0.5    to the right, improve=1.0803180, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.7807692, (0 missing)
##   Surrogate splits:
##       age < 48     to the left,  agree=0.938, adj=0.111, (0 split)
## 
## Node number 414: 12 observations
##   predicted class=B2  expected loss=0.4166667  P(node) =0.0006
##     class counts:     2     7     2     1     0
##    probabilities: 0.167 0.583 0.167 0.083 0.000 
## 
## Node number 415: 14 observations
##   predicted class=B3  expected loss=0.3571429  P(node) =0.0007
##     class counts:     1     3     9     1     0
##    probabilities: 0.071 0.214 0.643 0.071 0.000 
## 
## Node number 416: 307 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.3745928  P(node) =0.01535
##     class counts:   192    71    28    14     2
##    probabilities: 0.625 0.231 0.091 0.046 0.007 
##   left son=832 (163 obs) right son=833 (144 obs)
##   Primary splits:
##       diabetes          < 0.5    to the right, improve=1.8426850, (0 missing)
##       reimbursement2008 < 1595   to the right, improve=1.1555100, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.0463660, (0 missing)
##       cancer            < 0.5    to the right, improve=0.9571640, (0 missing)
##       age               < 88.5   to the left,  improve=0.9457736, (0 missing)
##   Surrogate splits:
##       age               < 75.5   to the right, agree=0.557, adj=0.056, (0 split)
##       reimbursement2008 < 1885   to the left,  agree=0.544, adj=0.028, (0 split)
## 
## Node number 417: 99 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.4747475  P(node) =0.00495
##     class counts:    52    34     7     5     1
##    probabilities: 0.525 0.343 0.071 0.051 0.010 
##   left son=834 (11 obs) right son=835 (88 obs)
##   Primary splits:
##       copd              < 0.5    to the right, improve=1.8888890, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.2998090, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.2183150, (0 missing)
##       reimbursement2008 < 2015   to the left,  improve=1.1747840, (0 missing)
##       age               < 88.5   to the left,  improve=0.8989783, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1615   to the left,  agree=0.909, adj=0.182, (0 split)
## 
## Node number 418: 261 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.4482759  P(node) =0.01305
##     class counts:   144    73    28    15     1
##    probabilities: 0.552 0.280 0.107 0.057 0.004 
##   left son=836 (228 obs) right son=837 (33 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=4.050652, (0 missing)
##       age               < 71.5   to the left,  improve=2.377089, (0 missing)
##       reimbursement2008 < 2485   to the left,  improve=1.974154, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.943678, (0 missing)
##       copd              < 0.5    to the left,  improve=1.910651, (0 missing)
## 
## Node number 419: 182 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.6098901  P(node) =0.0091
##     class counts:    71    68    29    11     3
##    probabilities: 0.390 0.374 0.159 0.060 0.016 
##   left son=838 (146 obs) right son=839 (36 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.1312160, (0 missing)
##       age               < 56.5   to the right, improve=2.0550500, (0 missing)
##       reimbursement2008 < 2235   to the left,  improve=1.8121880, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.1570780, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.5846992, (0 missing)
## 
## Node number 426: 15 observations
##   predicted class=B1  expected loss=0.5333333  P(node) =0.00075
##     class counts:     7     4     2     2     0
##    probabilities: 0.467 0.267 0.133 0.133 0.000 
## 
## Node number 427: 10 observations
##   predicted class=B2  expected loss=0.3  P(node) =0.0005
##     class counts:     2     7     0     1     0
##    probabilities: 0.200 0.700 0.000 0.100 0.000 
## 
## Node number 428: 162 observations,    complexity param=0.001064801
##   predicted class=B1  expected loss=0.5308642  P(node) =0.0081
##     class counts:    76    53    20    12     1
##    probabilities: 0.469 0.327 0.123 0.074 0.006 
##   left son=856 (76 obs) right son=857 (86 obs)
##   Primary splits:
##       reimbursement2008 < 1975   to the left,  improve=5.6805310, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.0157000, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8458215, (0 missing)
##       age               < 48.5   to the left,  improve=0.7356979, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.5696349, (0 missing)
##   Surrogate splits:
##       age          < 65.5   to the left,  agree=0.580, adj=0.105, (0 split)
##       osteoporosis < 0.5    to the right, agree=0.549, adj=0.039, (0 split)
##       diabetes     < 0.5    to the left,  agree=0.537, adj=0.013, (0 split)
##       stroke       < 0.5    to the right, agree=0.537, adj=0.013, (0 split)
## 
## Node number 429: 136 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.5294118  P(node) =0.0068
##     class counts:    46    64    23     3     0
##    probabilities: 0.338 0.471 0.169 0.022 0.000 
##   left son=858 (117 obs) right son=859 (19 obs)
##   Primary splits:
##       reimbursement2008 < 1705   to the right, improve=2.1418260, (0 missing)
##       age               < 77.5   to the right, improve=1.2623840, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7897266, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6677123, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.6652316, (0 missing)
## 
## Node number 432: 68 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.3529412  P(node) =0.0034
##     class counts:    44    18     3     3     0
##    probabilities: 0.647 0.265 0.044 0.044 0.000 
##   left son=864 (21 obs) right son=865 (47 obs)
##   Primary splits:
##       age               < 64.5   to the right, improve=2.2730500, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.3235290, (0 missing)
##       depression        < 0.5    to the left,  improve=1.1164500, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.9705882, (0 missing)
##       reimbursement2008 < 3195   to the left,  improve=0.9338624, (0 missing)
## 
## Node number 433: 213 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.4835681  P(node) =0.01065
##     class counts:   110    60    32     9     2
##    probabilities: 0.516 0.282 0.150 0.042 0.009 
##   left son=866 (92 obs) right son=867 (121 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=2.4788660, (0 missing)
##       reimbursement2008 < 3155   to the right, improve=1.9913470, (0 missing)
##       age               < 69.5   to the right, improve=1.9417030, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.1103130, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7492129, (0 missing)
##   Surrogate splits:
##       age               < 83.5   to the right, agree=0.577, adj=0.022, (0 split)
##       reimbursement2008 < 2535   to the left,  agree=0.573, adj=0.011, (0 split)
## 
## Node number 434: 10 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0005
##     class counts:     5     3     2     0     0
##    probabilities: 0.500 0.300 0.200 0.000 0.000 
## 
## Node number 435: 26 observations
##   predicted class=B2  expected loss=0.2692308  P(node) =0.0013
##     class counts:     3    19     4     0     0
##    probabilities: 0.115 0.731 0.154 0.000 0.000 
## 
## Node number 436: 146 observations,    complexity param=0.0006084576
##   predicted class=B1  expected loss=0.5547945  P(node) =0.0073
##     class counts:    65    52    16    13     0
##    probabilities: 0.445 0.356 0.110 0.089 0.000 
##   left son=872 (133 obs) right son=873 (13 obs)
##   Primary splits:
##       reimbursement2008 < 2585   to the right, improve=2.3843300, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.0271490, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.0118830, (0 missing)
##       depression        < 0.5    to the left,  improve=0.8908181, (0 missing)
##       age               < 74.5   to the left,  improve=0.8215784, (0 missing)
## 
## Node number 437: 67 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6567164  P(node) =0.00335
##     class counts:    18    23    17     9     0
##    probabilities: 0.269 0.343 0.254 0.134 0.000 
##   left son=874 (11 obs) right son=875 (56 obs)
##   Primary splits:
##       reimbursement2008 < 2605   to the left,  improve=0.8274375, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8104509, (0 missing)
##       age               < 58.5   to the left,  improve=0.7605544, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5110835, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=0.2925650, (0 missing)
##   Surrogate splits:
##       age < 47.5   to the left,  agree=0.881, adj=0.273, (0 split)
## 
## Node number 438: 57 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.4912281  P(node) =0.00285
##     class counts:    16    29     9     3     0
##    probabilities: 0.281 0.509 0.158 0.053 0.000 
##   left son=876 (41 obs) right son=877 (16 obs)
##   Primary splits:
##       reimbursement2008 < 2735   to the right, improve=2.1723900, (0 missing)
##       age               < 70.5   to the left,  improve=1.5686010, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.1967800, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6143996, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=0.4557416, (0 missing)
## 
## Node number 439: 27 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.5555556  P(node) =0.00135
##     class counts:     4    12    11     0     0
##    probabilities: 0.148 0.444 0.407 0.000 0.000 
##   left son=878 (9 obs) right son=879 (18 obs)
##   Primary splits:
##       age               < 84.5   to the right, improve=1.92592600, (0 missing)
##       reimbursement2008 < 3145   to the right, improve=0.29259260, (0 missing)
##       depression        < 0.5    to the left,  improve=0.29259260, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.20797720, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.07494553, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2695   to the left,  agree=0.741, adj=0.222, (0 split)
## 
## Node number 440: 150 observations,    complexity param=0.0002788764
##   predicted class=B2  expected loss=0.5533333  P(node) =0.0075
##     class counts:    50    67    27     5     1
##    probabilities: 0.333 0.447 0.180 0.033 0.007 
##   left son=880 (142 obs) right son=881 (8 obs)
##   Primary splits:
##       age               < 89.5   to the left,  improve=1.4895310, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.4218900, (0 missing)
##       reimbursement2008 < 2825   to the right, improve=1.3233330, (0 missing)
##       copd              < 0.5    to the left,  improve=1.2090920, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.9791534, (0 missing)
## 
## Node number 441: 7 observations
##   predicted class=B2  expected loss=0.1428571  P(node) =0.00035
##     class counts:     0     6     1     0     0
##    probabilities: 0.000 0.857 0.143 0.000 0.000 
## 
## Node number 444: 70 observations,    complexity param=0.000190143
##   predicted class=B2  expected loss=0.5  P(node) =0.0035
##     class counts:    22    35     8     4     1
##    probabilities: 0.314 0.500 0.114 0.057 0.014 
##   left son=888 (40 obs) right son=889 (30 obs)
##   Primary splits:
##       reimbursement2008 < 3265   to the left,  improve=2.1952380, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8206310, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.8196825, (0 missing)
##       copd              < 0.5    to the left,  improve=0.7659533, (0 missing)
##       age               < 82.5   to the right, improve=0.6993816, (0 missing)
##   Surrogate splits:
##       age           < 54.5   to the right, agree=0.614, adj=0.100, (0 split)
##       cancer        < 0.5    to the left,  agree=0.614, adj=0.100, (0 split)
##       heart.failure < 0.5    to the right, agree=0.614, adj=0.100, (0 split)
##       depression    < 0.5    to the right, agree=0.600, adj=0.067, (0 split)
## 
## Node number 445: 11 observations
##   predicted class=B2  expected loss=0.2727273  P(node) =0.00055
##     class counts:     1     8     0     2     0
##    probabilities: 0.091 0.727 0.000 0.182 0.000 
## 
## Node number 448: 120 observations,    complexity param=0.0001014096
##   predicted class=B1  expected loss=0.275  P(node) =0.006
##     class counts:    87    21     8     4     0
##    probabilities: 0.725 0.175 0.067 0.033 0.000 
##   left son=896 (26 obs) right son=897 (94 obs)
##   Primary splits:
##       reimbursement2008 < 8195   to the right, improve=1.9843150, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.6375210, (0 missing)
##       age               < 49.5   to the right, improve=1.1599100, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.1550330, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5544872, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.975, adj=0.885, (0 split)
## 
## Node number 449: 210 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.4380952  P(node) =0.0105
##     class counts:   118    56    28     6     2
##    probabilities: 0.562 0.267 0.133 0.029 0.010 
##   left son=898 (89 obs) right son=899 (121 obs)
##   Primary splits:
##       reimbursement2008 < 7060   to the right, improve=1.5649970, (0 missing)
##       age               < 59.5   to the right, improve=0.9328321, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.8837035, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.5471253, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4479437, (0 missing)
##   Surrogate splits:
##       bucket2008    < 2.5    to the right, agree=0.952, adj=0.888, (0 split)
##       kidney        < 0.5    to the right, agree=0.662, adj=0.202, (0 split)
##       age           < 83.5   to the right, agree=0.619, adj=0.101, (0 split)
##       heart.failure < 0.5    to the right, agree=0.619, adj=0.101, (0 split)
##       copd          < 0.5    to the right, agree=0.614, adj=0.090, (0 split)
## 
## Node number 450: 15 observations
##   predicted class=B1  expected loss=0.2  P(node) =0.00075
##     class counts:    12     1     1     1     0
##    probabilities: 0.800 0.067 0.067 0.067 0.000 
## 
## Node number 451: 74 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.5540541  P(node) =0.0037
##     class counts:    33    33     5     2     1
##    probabilities: 0.446 0.446 0.068 0.027 0.014 
##   left son=902 (60 obs) right son=903 (14 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.3193050, (0 missing)
##       age               < 66.5   to the left,  improve=1.1497330, (0 missing)
##       reimbursement2008 < 6655   to the left,  improve=0.9978265, (0 missing)
##       ihd               < 0.5    to the right, improve=0.5988288, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4239269, (0 missing)
##   Surrogate splits:
##       age               < 90.5   to the left,  agree=0.851, adj=0.214, (0 split)
##       reimbursement2008 < 11700  to the left,  agree=0.838, adj=0.143, (0 split)
## 
## Node number 452: 27 observations
##   predicted class=B1  expected loss=0.2962963  P(node) =0.00135
##     class counts:    19     4     1     3     0
##    probabilities: 0.704 0.148 0.037 0.111 0.000 
## 
## Node number 453: 31 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.6129032  P(node) =0.00155
##     class counts:    12    11     7     1     0
##    probabilities: 0.387 0.355 0.226 0.032 0.000 
##   left son=906 (16 obs) right son=907 (15 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the right, improve=0.9637097, (0 missing)
##       copd              < 0.5    to the right, improve=0.9101382, (0 missing)
##       reimbursement2008 < 4635   to the right, improve=0.7294660, (0 missing)
##       ihd               < 0.5    to the right, improve=0.6841642, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5193819, (0 missing)
##   Surrogate splits:
##       kidney            < 0.5    to the right, agree=0.710, adj=0.400, (0 split)
##       reimbursement2008 < 5195   to the right, agree=0.677, adj=0.333, (0 split)
##       age               < 68     to the right, agree=0.613, adj=0.200, (0 split)
##       ihd               < 0.5    to the right, agree=0.613, adj=0.200, (0 split)
##       copd              < 0.5    to the right, agree=0.581, adj=0.133, (0 split)
## 
## Node number 454: 14 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.0007
##     class counts:     8     3     2     1     0
##    probabilities: 0.571 0.214 0.143 0.071 0.000 
## 
## Node number 455: 72 observations,    complexity param=0.0003549336
##   predicted class=B2  expected loss=0.5972222  P(node) =0.0036
##     class counts:    22    29    19     2     0
##    probabilities: 0.306 0.403 0.264 0.028 0.000 
##   left son=910 (18 obs) right son=911 (54 obs)
##   Primary splits:
##       reimbursement2008 < 4780   to the left,  improve=1.4537040, (0 missing)
##       copd              < 0.5    to the right, improve=1.3585470, (0 missing)
##       age               < 80.5   to the right, improve=0.9255324, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.7387668, (0 missing)
##       kidney            < 0.5    to the right, improve=0.4950505, (0 missing)
## 
## Node number 456: 10 observations
##   predicted class=B2  expected loss=0.3  P(node) =0.0005
##     class counts:     2     7     1     0     0
##    probabilities: 0.200 0.700 0.100 0.000 0.000 
## 
## Node number 457: 32 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5  P(node) =0.0016
##     class counts:    16     8     3     5     0
##    probabilities: 0.500 0.250 0.094 0.156 0.000 
##   left son=914 (25 obs) right son=915 (7 obs)
##   Primary splits:
##       age               < 64.5   to the right, improve=1.3717860, (0 missing)
##       copd              < 0.5    to the left,  improve=1.3541670, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.8125000, (0 missing)
##       reimbursement2008 < 5140   to the left,  improve=0.5882937, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.2860714, (0 missing)
##   Surrogate splits:
##       arthritis < 0.5    to the left,  agree=0.812, adj=0.143, (0 split)
## 
## Node number 462: 12 observations
##   predicted class=B1  expected loss=0.5833333  P(node) =0.0006
##     class counts:     5     2     3     2     0
##    probabilities: 0.417 0.167 0.250 0.167 0.000 
## 
## Node number 463: 11 observations
##   predicted class=B3  expected loss=0.4545455  P(node) =0.00055
##     class counts:     1     4     6     0     0
##    probabilities: 0.091 0.364 0.545 0.000 0.000 
## 
## Node number 468: 72 observations,    complexity param=0.0006084576
##   predicted class=B2  expected loss=0.5277778  P(node) =0.0036
##     class counts:    28    34     7     3     0
##    probabilities: 0.389 0.472 0.097 0.042 0.000 
##   left son=936 (27 obs) right son=937 (45 obs)
##   Primary splits:
##       reimbursement2008 < 7260   to the right, improve=3.153704, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.757692, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.512060, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.494255, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.126923, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.903, adj=0.741, (0 split)
##       age        < 57.5   to the left,  agree=0.639, adj=0.037, (0 split)
##       kidney     < 0.5    to the right, agree=0.639, adj=0.037, (0 split)
## 
## Node number 469: 64 observations,    complexity param=0.0003549336
##   predicted class=B2  expected loss=0.5  P(node) =0.0032
##     class counts:    12    32    16     4     0
##    probabilities: 0.188 0.500 0.250 0.062 0.000 
##   left son=938 (12 obs) right son=939 (52 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=2.2692310, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.4314290, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.7790989, (0 missing)
##       reimbursement2008 < 23405  to the right, improve=0.7180451, (0 missing)
##       age               < 76.5   to the left,  improve=0.6937984, (0 missing)
## 
## Node number 470: 46 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.5217391  P(node) =0.0023
##     class counts:    22     9    10     5     0
##    probabilities: 0.478 0.196 0.217 0.109 0.000 
##   left son=940 (13 obs) right son=941 (33 obs)
##   Primary splits:
##       age               < 91.5   to the right, improve=2.1375290, (0 missing)
##       reimbursement2008 < 13835  to the left,  improve=1.6227110, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.1379310, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.9519520, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.6946237, (0 missing)
## 
## Node number 471: 11 observations
##   predicted class=B2  expected loss=0.4545455  P(node) =0.00055
##     class counts:     2     6     3     0     0
##    probabilities: 0.182 0.545 0.273 0.000 0.000 
## 
## Node number 478: 79 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.556962  P(node) =0.00395
##     class counts:    15    35    23     6     0
##    probabilities: 0.190 0.443 0.291 0.076 0.000 
##   left son=956 (41 obs) right son=957 (38 obs)
##   Primary splits:
##       age               < 75.5   to the left,  improve=0.9917453, (0 missing)
##       reimbursement2008 < 4785   to the left,  improve=0.9835014, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.7155960, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.6911068, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6784535, (0 missing)
##   Surrogate splits:
##       arthritis         < 0.5    to the left,  agree=0.658, adj=0.289, (0 split)
##       reimbursement2008 < 8635   to the left,  agree=0.633, adj=0.237, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.608, adj=0.184, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.582, adj=0.132, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.557, adj=0.079, (0 split)
## 
## Node number 479: 7 observations
##   predicted class=B1  expected loss=0.5714286  P(node) =0.00035
##     class counts:     3     1     1     2     0
##    probabilities: 0.429 0.143 0.143 0.286 0.000 
## 
## Node number 480: 199 observations,    complexity param=0.0008746577
##   predicted class=B1  expected loss=0.5477387  P(node) =0.00995
##     class counts:    90    72    32     5     0
##    probabilities: 0.452 0.362 0.161 0.025 0.000 
##   left son=960 (155 obs) right son=961 (44 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=4.0942290, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.4154020, (0 missing)
##       reimbursement2008 < 7230   to the right, improve=1.3220170, (0 missing)
##       age               < 62.5   to the right, improve=0.9109503, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.7457594, (0 missing)
##   Surrogate splits:
##       age < 31.5   to the right, agree=0.789, adj=0.045, (0 split)
## 
## Node number 481: 78 observations,    complexity param=0.000507048
##   predicted class=B1  expected loss=0.6923077  P(node) =0.0039
##     class counts:    24    19    20    14     1
##    probabilities: 0.308 0.244 0.256 0.179 0.013 
##   left son=962 (52 obs) right son=963 (26 obs)
##   Primary splits:
##       reimbursement2008 < 11475  to the right, improve=1.756410, (0 missing)
##       age               < 65.5   to the right, improve=1.591079, (0 missing)
##       depression        < 0.5    to the left,  improve=1.545455, (0 missing)
##       copd              < 0.5    to the left,  improve=1.292572, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.277778, (0 missing)
##   Surrogate splits:
##       ihd < 0.5    to the right, agree=0.705, adj=0.115, (0 split)
##       age < 49.5   to the right, agree=0.679, adj=0.038, (0 split)
## 
## Node number 482: 327 observations,    complexity param=0.0008746577
##   predicted class=B1  expected loss=0.6116208  P(node) =0.01635
##     class counts:   127   125    50    22     3
##    probabilities: 0.388 0.382 0.153 0.067 0.009 
##   left son=964 (170 obs) right son=965 (157 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=2.493752, (0 missing)
##       reimbursement2008 < 5355   to the left,  improve=2.213439, (0 missing)
##       age               < 97.5   to the left,  improve=2.016707, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.460516, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.183698, (0 missing)
##   Surrogate splits:
##       alzheimers        < 0.5    to the left,  agree=0.584, adj=0.134, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.572, adj=0.108, (0 split)
##       reimbursement2008 < 9565   to the left,  agree=0.566, adj=0.096, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.557, adj=0.076, (0 split)
##       age               < 80.5   to the left,  agree=0.554, adj=0.070, (0 split)
## 
## Node number 483: 187 observations,    complexity param=0.000380286
##   predicted class=B2  expected loss=0.4545455  P(node) =0.00935
##     class counts:    51   102    27     7     0
##    probabilities: 0.273 0.545 0.144 0.037 0.000 
##   left son=966 (74 obs) right son=967 (113 obs)
##   Primary splits:
##       age               < 77.5   to the left,  improve=1.8473350, (0 missing)
##       reimbursement2008 < 4720   to the left,  improve=1.8297120, (0 missing)
##       stroke            < 0.5    to the right, improve=0.8760224, (0 missing)
##       depression        < 0.5    to the right, improve=0.8148550, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.6872708, (0 missing)
## 
## Node number 486: 120 observations,    complexity param=0.0005324004
##   predicted class=B2  expected loss=0.6166667  P(node) =0.006
##     class counts:    25    46    38    11     0
##    probabilities: 0.208 0.383 0.317 0.092 0.000 
##   left son=972 (8 obs) right son=973 (112 obs)
##   Primary splits:
##       age               < 59.5   to the left,  improve=3.0630950, (0 missing)
##       reimbursement2008 < 6810   to the left,  improve=2.3493340, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.5126620, (0 missing)
##       depression        < 0.5    to the left,  improve=1.2818450, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.9859477, (0 missing)
## 
## Node number 487: 14 observations
##   predicted class=B3  expected loss=0.3571429  P(node) =0.0007
##     class counts:     3     2     9     0     0
##    probabilities: 0.214 0.143 0.643 0.000 0.000 
## 
## Node number 492: 183 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.557377  P(node) =0.00915
##     class counts:    52    81    23    23     4
##    probabilities: 0.284 0.443 0.126 0.126 0.022 
##   left son=984 (56 obs) right son=985 (127 obs)
##   Primary splits:
##       reimbursement2008 < 11200  to the right, improve=1.3922150, (0 missing)
##       age               < 67.5   to the right, improve=1.3360660, (0 missing)
##       copd              < 0.5    to the left,  improve=1.2442960, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.9452905, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9450073, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.907, adj=0.696, (0 split)
## 
## Node number 493: 99 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4747475  P(node) =0.00495
##     class counts:    16    52    21    10     0
##    probabilities: 0.162 0.525 0.212 0.101 0.000 
##   left son=986 (37 obs) right son=987 (62 obs)
##   Primary splits:
##       age               < 79.5   to the right, improve=2.3556310, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.3800430, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.2000000, (0 missing)
##       reimbursement2008 < 25605  to the right, improve=1.1394690, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9554113, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 13065  to the right, agree=0.657, adj=0.081, (0 split)
## 
## Node number 494: 241 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5435685  P(node) =0.01205
##     class counts:    46   110    62    21     2
##    probabilities: 0.191 0.456 0.257 0.087 0.008 
##   left son=988 (16 obs) right son=989 (225 obs)
##   Primary splits:
##       age               < 54.5   to the left,  improve=1.3463230, (0 missing)
##       reimbursement2008 < 4070   to the right, improve=1.3125650, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.3020150, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.0773410, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6861288, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 52960  to the right, agree=0.938, adj=0.062, (0 split)
##       bucket2008        < 4.5    to the right, agree=0.938, adj=0.062, (0 split)
## 
## Node number 495: 12 observations
##   predicted class=B3  expected loss=0.4166667  P(node) =0.0006
##     class counts:     0     5     7     0     0
##    probabilities: 0.000 0.417 0.583 0.000 0.000 
## 
## Node number 496: 346 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6531792  P(node) =0.0173
##     class counts:    88   120    71    57    10
##    probabilities: 0.254 0.347 0.205 0.165 0.029 
##   left son=992 (67 obs) right son=993 (279 obs)
##   Primary splits:
##       age               < 85.5   to the right, improve=2.853034, (0 missing)
##       reimbursement2008 < 6780   to the left,  improve=2.493960, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.888712, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.770580, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.127732, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 15040  to the right, agree=0.812, adj=0.03, (0 split)
## 
## Node number 497: 266 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.5902256  P(node) =0.0133
##     class counts:    50   109    68    33     6
##    probabilities: 0.188 0.410 0.256 0.124 0.023 
##   left son=994 (19 obs) right son=995 (247 obs)
##   Primary splits:
##       age               < 92.5   to the right, improve=3.1654140, (0 missing)
##       reimbursement2008 < 6185   to the left,  improve=2.8527200, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.0112500, (0 missing)
##       ihd               < 0.5    to the right, improve=0.9988659, (0 missing)
##       depression        < 0.5    to the right, improve=0.8363985, (0 missing)
## 
## Node number 498: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     0     4     3     0     0
##    probabilities: 0.000 0.571 0.429 0.000 0.000 
## 
## Node number 499: 19 observations
##   predicted class=B3  expected loss=0.3684211  P(node) =0.00095
##     class counts:     1     3    12     3     0
##    probabilities: 0.053 0.158 0.632 0.158 0.000 
## 
## Node number 500: 11 observations
##   predicted class=B2  expected loss=0.09090909  P(node) =0.00055
##     class counts:     0    10     0     1     0
##    probabilities: 0.000 0.909 0.000 0.091 0.000 
## 
## Node number 501: 132 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.4318182  P(node) =0.0066
##     class counts:    20    75    22    14     1
##    probabilities: 0.152 0.568 0.167 0.106 0.008 
##   left son=1002 (107 obs) right son=1003 (25 obs)
##   Primary splits:
##       reimbursement2008 < 4815   to the left,  improve=1.3622030, (0 missing)
##       age               < 80.5   to the right, improve=1.1112760, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7506887, (0 missing)
##       copd              < 0.5    to the right, improve=0.7453568, (0 missing)
##       cancer            < 0.5    to the right, improve=0.5247008, (0 missing)
## 
## Node number 502: 24 observations,    complexity param=0.0002028192
##   predicted class=B3  expected loss=0.6666667  P(node) =0.0012
##     class counts:     7     7     8     2     0
##    probabilities: 0.292 0.292 0.333 0.083 0.000 
##   left son=1004 (16 obs) right son=1005 (8 obs)
##   Primary splits:
##       age               < 70     to the right, improve=1.458333, (0 missing)
##       reimbursement2008 < 7185   to the right, improve=1.305556, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.261111, (0 missing)
##       depression        < 0.5    to the right, improve=1.083333, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.083333, (0 missing)
## 
## Node number 503: 285 observations,    complexity param=0.0002028192
##   predicted class=B2  expected loss=0.5263158  P(node) =0.01425
##     class counts:    29   135    77    38     6
##    probabilities: 0.102 0.474 0.270 0.133 0.021 
##   left son=1006 (253 obs) right son=1007 (32 obs)
##   Primary splits:
##       reimbursement2008 < 5725   to the right, improve=1.2734940, (0 missing)
##       age               < 95.5   to the right, improve=1.2461000, (0 missing)
##       copd              < 0.5    to the left,  improve=1.1568740, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.6666667, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.6302632, (0 missing)
## 
## Node number 504: 11 observations
##   predicted class=B1  expected loss=0.1818182  P(node) =0.00055
##     class counts:     9     0     1     1     0
##    probabilities: 0.818 0.000 0.091 0.091 0.000 
## 
## Node number 505: 9 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.00045
##     class counts:     2     5     0     2     0
##    probabilities: 0.222 0.556 0.000 0.222 0.000 
## 
## Node number 506: 20 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.4  P(node) =0.001
##     class counts:     1    12     2     4     1
##    probabilities: 0.050 0.600 0.100 0.200 0.050 
##   left son=1012 (13 obs) right son=1013 (7 obs)
##   Primary splits:
##       reimbursement2008 < 22825  to the left,  improve=4.1615380, (0 missing)
##       copd              < 0.5    to the right, improve=1.2757580, (0 missing)
##       age               < 68.5   to the right, improve=0.2833333, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.1000000, (0 missing)
##   Surrogate splits:
##       age          < 72.5   to the left,  agree=0.75, adj=0.286, (0 split)
##       osteoporosis < 0.5    to the left,  agree=0.75, adj=0.286, (0 split)
## 
## Node number 507: 13 observations
##   predicted class=B4  expected loss=0.4615385  P(node) =0.00065
##     class counts:     4     1     1     7     0
##    probabilities: 0.308 0.077 0.077 0.538 0.000 
## 
## Node number 508: 233 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6866953  P(node) =0.01165
##     class counts:    48    73    49    55     8
##    probabilities: 0.206 0.313 0.210 0.236 0.034 
##   left son=1016 (95 obs) right son=1017 (138 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.100995, (0 missing)
##       reimbursement2008 < 25650  to the right, improve=1.969720, (0 missing)
##       age               < 89.5   to the right, improve=1.419602, (0 missing)
##       stroke            < 0.5    to the right, improve=1.223362, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.077810, (0 missing)
##   Surrogate splits:
##       heart.failure < 0.5    to the left,  agree=0.609, adj=0.042, (0 split)
##       age           < 53.5   to the left,  agree=0.601, adj=0.021, (0 split)
## 
## Node number 509: 163 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6196319  P(node) =0.00815
##     class counts:    18    62    50    24     9
##    probabilities: 0.110 0.380 0.307 0.147 0.055 
##   left son=1018 (140 obs) right son=1019 (23 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the right, improve=2.091784, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.893817, (0 missing)
##       age               < 65     to the right, improve=1.795615, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.116333, (0 missing)
##       reimbursement2008 < 16525  to the right, improve=1.100480, (0 missing)
## 
## Node number 510: 65 observations
##   predicted class=B2  expected loss=0.4307692  P(node) =0.00325
##     class counts:     7    37     7    10     4
##    probabilities: 0.108 0.569 0.108 0.154 0.062 
## 
## Node number 511: 422 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6492891  P(node) =0.0211
##     class counts:    30   148    97   126    21
##    probabilities: 0.071 0.351 0.230 0.299 0.050 
##   left son=1022 (91 obs) right son=1023 (331 obs)
##   Primary splits:
##       reimbursement2008 < 32040  to the left,  improve=2.8304840, (0 missing)
##       stroke            < 0.5    to the right, improve=2.0316160, (0 missing)
##       age               < 34.5   to the left,  improve=1.6984130, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9304072, (0 missing)
##       bucket2008        < 4.5    to the right, improve=0.8586131, (0 missing)
## 
## Node number 642: 801 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1585518  P(node) =0.04005
##     class counts:   674    73    40    12     2
##    probabilities: 0.841 0.091 0.050 0.015 0.002 
##   left son=1284 (94 obs) right son=1285 (707 obs)
##   Primary splits:
##       reimbursement2008 < 245    to the left,  improve=0.4516579, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.3483743, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.3415246, (0 missing)
##       age               < 83.5   to the right, improve=0.3232539, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.2952273, (0 missing)
## 
## Node number 643: 29 observations
##   predicted class=B1  expected loss=0.2758621  P(node) =0.00145
##     class counts:    21     7     1     0     0
##    probabilities: 0.724 0.241 0.034 0.000 0.000 
## 
## Node number 706: 149 observations
##   predicted class=B1  expected loss=0.1677852  P(node) =0.00745
##     class counts:   124    18     3     4     0
##    probabilities: 0.832 0.121 0.020 0.027 0.000 
## 
## Node number 707: 57 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3684211  P(node) =0.00285
##     class counts:    36    13     3     5     0
##    probabilities: 0.632 0.228 0.053 0.088 0.000 
##   left son=1414 (43 obs) right son=1415 (14 obs)
##   Primary splits:
##       age               < 83.5   to the left,  improve=2.8778340, (0 missing)
##       reimbursement2008 < 945    to the left,  improve=1.6818210, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7156433, (0 missing)
## 
## Node number 710: 76 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2763158  P(node) =0.0038
##     class counts:    55    16     3     2     0
##    probabilities: 0.724 0.211 0.039 0.026 0.000 
##   left son=1420 (9 obs) right son=1421 (67 obs)
##   Primary splits:
##       age               < 81     to the right, improve=0.8204155, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5009717, (0 missing)
##       kidney            < 0.5    to the right, improve=0.4025050, (0 missing)
##       reimbursement2008 < 775    to the left,  improve=0.2718808, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2404084, (0 missing)
## 
## Node number 711: 9 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.00045
##     class counts:     4     5     0     0     0
##    probabilities: 0.444 0.556 0.000 0.000 0.000 
## 
## Node number 720: 283 observations,    complexity param=5.07048e-05
##   predicted class=B1  expected loss=0.2120141  P(node) =0.01415
##     class counts:   223    29    22     9     0
##    probabilities: 0.788 0.102 0.078 0.032 0.000 
##   left son=1440 (27 obs) right son=1441 (256 obs)
##   Primary splits:
##       age               < 87.5   to the right, improve=0.7753638, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.5910595, (0 missing)
##       reimbursement2008 < 1315   to the right, improve=0.5333621, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4097368, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.3159337, (0 missing)
## 
## Node number 721: 166 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.2831325  P(node) =0.0083
##     class counts:   119    28    14     5     0
##    probabilities: 0.717 0.169 0.084 0.030 0.000 
##   left son=1442 (158 obs) right son=1443 (8 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=0.7746302, (0 missing)
##       age               < 73.5   to the right, improve=0.7080149, (0 missing)
##       reimbursement2008 < 1525   to the right, improve=0.3417250, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3081519, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.2090240, (0 missing)
## 
## Node number 722: 50 observations
##   predicted class=B1  expected loss=0.26  P(node) =0.0025
##     class counts:    37     7     4     2     0
##    probabilities: 0.740 0.140 0.080 0.040 0.000 
## 
## Node number 723: 87 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.3448276  P(node) =0.00435
##     class counts:    57    24     3     3     0
##    probabilities: 0.655 0.276 0.034 0.034 0.000 
##   left son=1446 (52 obs) right son=1447 (35 obs)
##   Primary splits:
##       reimbursement2008 < 1235   to the left,  improve=1.3847290, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.0449780, (0 missing)
##       age               < 56.5   to the left,  improve=0.4942529, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.3668719, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.2869269, (0 missing)
##   Surrogate splits:
##       age        < 66.5   to the left,  agree=0.621, adj=0.057, (0 split)
##       depression < 0.5    to the left,  agree=0.609, adj=0.029, (0 split)
## 
## Node number 724: 44 observations
##   predicted class=B1  expected loss=0.1818182  P(node) =0.0022
##     class counts:    36     5     1     1     1
##    probabilities: 0.818 0.114 0.023 0.023 0.023 
## 
## Node number 725: 99 observations,    complexity param=0.0001303838
##   predicted class=B1  expected loss=0.3434343  P(node) =0.00495
##     class counts:    65    23     7     3     1
##    probabilities: 0.657 0.232 0.071 0.030 0.010 
##   left son=1450 (88 obs) right son=1451 (11 obs)
##   Primary splits:
##       age               < 73.5   to the left,  improve=3.2020200, (0 missing)
##       kidney            < 0.5    to the left,  improve=1.8723440, (0 missing)
##       depression        < 0.5    to the left,  improve=1.3986170, (0 missing)
##       reimbursement2008 < 1495   to the left,  improve=0.6074520, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.4981241, (0 missing)
## 
## Node number 726: 17 observations
##   predicted class=B1  expected loss=0.3529412  P(node) =0.00085
##     class counts:    11     4     1     1     0
##    probabilities: 0.647 0.235 0.059 0.059 0.000 
## 
## Node number 727: 12 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0006
##     class counts:     3     6     2     1     0
##    probabilities: 0.250 0.500 0.167 0.083 0.000 
## 
## Node number 736: 455 observations
##   predicted class=B1  expected loss=0.2307692  P(node) =0.02275
##     class counts:   350    70    26     7     2
##    probabilities: 0.769 0.154 0.057 0.015 0.004 
## 
## Node number 737: 173 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3236994  P(node) =0.00865
##     class counts:   117    34    17     5     0
##    probabilities: 0.676 0.197 0.098 0.029 0.000 
##   left son=1474 (145 obs) right son=1475 (28 obs)
##   Primary splits:
##       reimbursement2008 < 820    to the right, improve=2.1496140, (0 missing)
##       copd              < 0.5    to the right, improve=1.2566750, (0 missing)
##       age               < 51     to the left,  improve=0.8052618, (0 missing)
##       depression        < 0.5    to the right, improve=0.7128829, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.2397510, (0 missing)
## 
## Node number 738: 52 observations
##   predicted class=B1  expected loss=0.3076923  P(node) =0.0026
##     class counts:    36    10     5     1     0
##    probabilities: 0.692 0.192 0.096 0.019 0.000 
## 
## Node number 739: 11 observations
##   predicted class=B2  expected loss=0.5454545  P(node) =0.00055
##     class counts:     4     5     2     0     0
##    probabilities: 0.364 0.455 0.182 0.000 0.000 
## 
## Node number 748: 28 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.0014
##     class counts:    16     7     2     3     0
##    probabilities: 0.571 0.250 0.071 0.107 0.000 
## 
## Node number 749: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     2     2     3     0     0
##    probabilities: 0.286 0.286 0.429 0.000 0.000 
## 
## Node number 756: 213 observations,    complexity param=6.084576e-05
##   predicted class=B1  expected loss=0.286385  P(node) =0.01065
##     class counts:   152    40    17     3     1
##    probabilities: 0.714 0.188 0.080 0.014 0.005 
##   left son=1512 (74 obs) right son=1513 (139 obs)
##   Primary splits:
##       age               < 79.5   to the right, improve=0.9593750, (0 missing)
##       reimbursement2008 < 1135   to the right, improve=0.8732722, (0 missing)
##       kidney            < 0.5    to the right, improve=0.6032588, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.5388738, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5312397, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1145   to the right, agree=0.676, adj=0.068, (0 split)
## 
## Node number 757: 97 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3917526  P(node) =0.00485
##     class counts:    59    25     7     6     0
##    probabilities: 0.608 0.258 0.072 0.062 0.000 
##   left son=1514 (68 obs) right son=1515 (29 obs)
##   Primary splits:
##       age               < 80.5   to the left,  improve=1.6903660, (0 missing)
##       reimbursement2008 < 825    to the left,  improve=1.2122050, (0 missing)
##       kidney            < 0.5    to the right, improve=0.6415946, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.3898343, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3406181, (0 missing)
##   Surrogate splits:
##       arthritis         < 0.5    to the left,  agree=0.711, adj=0.034, (0 split)
##       reimbursement2008 < 695    to the right, agree=0.711, adj=0.034, (0 split)
## 
## Node number 760: 242 observations
##   predicted class=B1  expected loss=0.3719008  P(node) =0.0121
##     class counts:   152    65    13    12     0
##    probabilities: 0.628 0.269 0.054 0.050 0.000 
## 
## Node number 761: 110 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4636364  P(node) =0.0055
##     class counts:    59    28    17     6     0
##    probabilities: 0.536 0.255 0.155 0.055 0.000 
##   left son=1522 (54 obs) right son=1523 (56 obs)
##   Primary splits:
##       age               < 70.5   to the left,  improve=1.6735210, (0 missing)
##       reimbursement2008 < 1215   to the right, improve=1.1616160, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.1244670, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.9812987, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5845740, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1435   to the right, agree=0.573, adj=0.130, (0 split)
##       kidney            < 0.5    to the right, agree=0.536, adj=0.056, (0 split)
##       copd              < 0.5    to the left,  agree=0.527, adj=0.037, (0 split)
##       alzheimers        < 0.5    to the right, agree=0.518, adj=0.019, (0 split)
##       heart.failure     < 0.5    to the right, agree=0.518, adj=0.019, (0 split)
## 
## Node number 762: 22 observations
##   predicted class=B1  expected loss=0.3636364  P(node) =0.0011
##     class counts:    14     2     4     1     1
##    probabilities: 0.636 0.091 0.182 0.045 0.045 
## 
## Node number 763: 8 observations
##   predicted class=B4  expected loss=0.625  P(node) =0.0004
##     class counts:     2     1     2     3     0
##    probabilities: 0.250 0.125 0.250 0.375 0.000 
## 
## Node number 768: 288 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.2743056  P(node) =0.0144
##     class counts:   209    43    28     8     0
##    probabilities: 0.726 0.149 0.097 0.028 0.000 
##   left son=1536 (47 obs) right son=1537 (241 obs)
##   Primary splits:
##       arthritis         < 0.5    to the right, improve=0.8439747, (0 missing)
##       reimbursement2008 < 1655   to the right, improve=0.6696734, (0 missing)
##       age               < 74.5   to the right, improve=0.6381027, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5456723, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.3289436, (0 missing)
## 
## Node number 769: 107 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3738318  P(node) =0.00535
##     class counts:    67    27    11     1     1
##    probabilities: 0.626 0.252 0.103 0.009 0.009 
##   left son=1538 (92 obs) right son=1539 (15 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=1.4783150, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7755357, (0 missing)
##       reimbursement2008 < 2050   to the right, improve=0.7622484, (0 missing)
##       age               < 52.5   to the right, improve=0.7367951, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.6885313, (0 missing)
## 
## Node number 770: 22 observations
##   predicted class=B1  expected loss=0.09090909  P(node) =0.0011
##     class counts:    20     2     0     0     0
##    probabilities: 0.909 0.091 0.000 0.000 0.000 
## 
## Node number 771: 100 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.46  P(node) =0.005
##     class counts:    54    28    11     7     0
##    probabilities: 0.540 0.280 0.110 0.070 0.000 
##   left son=1542 (72 obs) right son=1543 (28 obs)
##   Primary splits:
##       age               < 79.5   to the left,  improve=1.5182540, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.4808320, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.2877110, (0 missing)
##       reimbursement2008 < 2415   to the left,  improve=1.1369950, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.6141026, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2565   to the left,  agree=0.74, adj=0.071, (0 split)
## 
## Node number 778: 66 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.4090909  P(node) =0.0033
##     class counts:    39    23     3     0     1
##    probabilities: 0.591 0.348 0.045 0.000 0.015 
##   left son=1556 (41 obs) right son=1557 (25 obs)
##   Primary splits:
##       age               < 80.5   to the left,  improve=0.7254398, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.4378788, (0 missing)
##       reimbursement2008 < 3315   to the left,  improve=0.4004696, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3326730, (0 missing)
##       depression        < 0.5    to the left,  improve=0.3017677, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.667, adj=0.12, (0 split)
## 
## Node number 779: 7 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.00035
##     class counts:     5     0     1     1     0
##    probabilities: 0.714 0.000 0.143 0.143 0.000 
## 
## Node number 782: 7 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.00035
##     class counts:     4     3     0     0     0
##    probabilities: 0.571 0.429 0.000 0.000 0.000 
## 
## Node number 783: 19 observations
##   predicted class=B2  expected loss=0.3157895  P(node) =0.00095
##     class counts:     4    13     1     1     0
##    probabilities: 0.211 0.684 0.053 0.053 0.000 
## 
## Node number 790: 50 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.46  P(node) =0.0025
##     class counts:    27    16     2     4     1
##    probabilities: 0.540 0.320 0.040 0.080 0.020 
##   left son=1580 (26 obs) right son=1581 (24 obs)
##   Primary splits:
##       age               < 71.5   to the right, improve=1.2069230, (0 missing)
##       reimbursement2008 < 1800   to the right, improve=1.0050000, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.8916550, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.8085714, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2265   to the left,  agree=0.62, adj=0.208, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.56, adj=0.083, (0 split)
## 
## Node number 791: 8 observations
##   predicted class=B2  expected loss=0.625  P(node) =0.0004
##     class counts:     2     3     3     0     0
##    probabilities: 0.250 0.375 0.375 0.000 0.000 
## 
## Node number 794: 9 observations
##   predicted class=B1  expected loss=0.2222222  P(node) =0.00045
##     class counts:     7     1     1     0     0
##    probabilities: 0.778 0.111 0.111 0.000 0.000 
## 
## Node number 795: 121 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5702479  P(node) =0.00605
##     class counts:    52    42    23     3     1
##    probabilities: 0.430 0.347 0.190 0.025 0.008 
##   left son=1590 (113 obs) right son=1591 (8 obs)
##   Primary splits:
##       reimbursement2008 < 3190   to the left,  improve=1.4937290, (0 missing)
##       age               < 83.5   to the left,  improve=1.2045730, (0 missing)
##       arthritis         < 0.5    to the right, improve=1.1497890, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.1433640, (0 missing)
##       cancer            < 0.5    to the right, improve=0.5801522, (0 missing)
## 
## Node number 832: 163 observations
##   predicted class=B1  expected loss=0.3374233  P(node) =0.00815
##     class counts:   108    28    18     8     1
##    probabilities: 0.663 0.172 0.110 0.049 0.006 
## 
## Node number 833: 144 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.4166667  P(node) =0.0072
##     class counts:    84    43    10     6     1
##    probabilities: 0.583 0.299 0.069 0.042 0.007 
##   left son=1666 (86 obs) right son=1667 (58 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=2.003041, (0 missing)
##       reimbursement2008 < 2295   to the left,  improve=1.394463, (0 missing)
##       age               < 96     to the right, improve=1.318865, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.140392, (0 missing)
##       copd              < 0.5    to the left,  improve=1.104582, (0 missing)
##   Surrogate splits:
##       kidney            < 0.5    to the left,  agree=0.632, adj=0.086, (0 split)
##       age               < 84.5   to the left,  agree=0.618, adj=0.052, (0 split)
##       reimbursement2008 < 2475   to the left,  agree=0.604, adj=0.017, (0 split)
## 
## Node number 834: 11 observations
##   predicted class=B1  expected loss=0.1818182  P(node) =0.00055
##     class counts:     9     1     1     0     0
##    probabilities: 0.818 0.091 0.091 0.000 0.000 
## 
## Node number 835: 88 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.5113636  P(node) =0.0044
##     class counts:    43    33     6     5     1
##    probabilities: 0.489 0.375 0.068 0.057 0.011 
##   left son=1670 (63 obs) right son=1671 (25 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=1.364329, (0 missing)
##       age               < 88.5   to the left,  improve=1.315651, (0 missing)
##       reimbursement2008 < 1675   to the right, improve=1.302389, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.227954, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.034774, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1665   to the right, agree=0.739, adj=0.08, (0 split)
## 
## Node number 836: 228 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.4078947  P(node) =0.0114
##     class counts:   135    61    20    11     1
##    probabilities: 0.592 0.268 0.088 0.048 0.004 
##   left son=1672 (218 obs) right son=1673 (10 obs)
##   Primary splits:
##       age               < 43.5   to the right, improve=2.3332050, (0 missing)
##       reimbursement2008 < 2485   to the left,  improve=2.1917580, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.7231690, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4130781, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3314113, (0 missing)
## 
## Node number 837: 33 observations,    complexity param=0.000380286
##   predicted class=B2  expected loss=0.6363636  P(node) =0.00165
##     class counts:     9    12     8     4     0
##    probabilities: 0.273 0.364 0.242 0.121 0.000 
##   left son=1674 (26 obs) right son=1675 (7 obs)
##   Primary splits:
##       age               < 72.5   to the left,  improve=2.8235100, (0 missing)
##       reimbursement2008 < 2185   to the right, improve=1.9883450, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.3051950, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.9114219, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5432900, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.848, adj=0.286, (0 split)
## 
## Node number 838: 146 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5821918  P(node) =0.0073
##     class counts:    56    61    19     8     2
##    probabilities: 0.384 0.418 0.130 0.055 0.014 
##   left son=1676 (115 obs) right son=1677 (31 obs)
##   Primary splits:
##       reimbursement2008 < 2235   to the left,  improve=1.5612480, (0 missing)
##       age               < 57     to the right, improve=1.4223930, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.7955683, (0 missing)
##       cancer            < 0.5    to the right, improve=0.5672709, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4457929, (0 missing)
## 
## Node number 839: 36 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.5833333  P(node) =0.0018
##     class counts:    15     7    10     3     1
##    probabilities: 0.417 0.194 0.278 0.083 0.028 
##   left son=1678 (11 obs) right son=1679 (25 obs)
##   Primary splits:
##       age               < 69.5   to the right, improve=1.3915150, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.1487180, (0 missing)
##       reimbursement2008 < 1805   to the left,  improve=1.0180620, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.8888889, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.2095875, (0 missing)
## 
## Node number 856: 76 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.3684211  P(node) =0.0038
##     class counts:    48    18     4     5     1
##    probabilities: 0.632 0.237 0.053 0.066 0.013 
##   left son=1712 (62 obs) right son=1713 (14 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=1.9467620, (0 missing)
##       reimbursement2008 < 1865   to the right, improve=1.2898500, (0 missing)
##       age               < 65.5   to the right, improve=1.1346230, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.9830044, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8057033, (0 missing)
## 
## Node number 857: 86 observations,    complexity param=0.0006084576
##   predicted class=B2  expected loss=0.5930233  P(node) =0.0043
##     class counts:    28    35    16     7     0
##    probabilities: 0.326 0.407 0.186 0.081 0.000 
##   left son=1714 (54 obs) right son=1715 (32 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=2.0120050, (0 missing)
##       reimbursement2008 < 2425   to the right, improve=1.7270100, (0 missing)
##       age               < 62.5   to the right, improve=1.4082940, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.0133720, (0 missing)
##       kidney            < 0.5    to the right, improve=0.7368141, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1995   to the right, agree=0.64, adj=0.031, (0 split)
## 
## Node number 858: 117 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.4871795  P(node) =0.00585
##     class counts:    39    60    17     1     0
##    probabilities: 0.333 0.513 0.145 0.009 0.000 
##   left son=1716 (8 obs) right son=1717 (109 obs)
##   Primary splits:
##       reimbursement2008 < 2445   to the right, improve=1.3278250, (0 missing)
##       age               < 77.5   to the right, improve=0.8223648, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.6487584, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5676773, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.3698183, (0 missing)
## 
## Node number 859: 19 observations
##   predicted class=B1  expected loss=0.6315789  P(node) =0.00095
##     class counts:     7     4     6     2     0
##    probabilities: 0.368 0.211 0.316 0.105 0.000 
## 
## Node number 864: 21 observations
##   predicted class=B1  expected loss=0.1428571  P(node) =0.00105
##     class counts:    18     2     0     1     0
##    probabilities: 0.857 0.095 0.000 0.048 0.000 
## 
## Node number 865: 47 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4468085  P(node) =0.00235
##     class counts:    26    16     3     2     0
##    probabilities: 0.553 0.340 0.064 0.043 0.000 
##   left son=1730 (37 obs) right son=1731 (10 obs)
##   Primary splits:
##       reimbursement2008 < 2765   to the right, improve=1.2287520, (0 missing)
##       depression        < 0.5    to the left,  improve=1.1399940, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.1047280, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7825059, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.7595591, (0 missing)
## 
## Node number 866: 92 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.3804348  P(node) =0.0046
##     class counts:    57    21    10     4     0
##    probabilities: 0.620 0.228 0.109 0.043 0.000 
##   left son=1732 (23 obs) right son=1733 (69 obs)
##   Primary splits:
##       reimbursement2008 < 3170   to the right, improve=1.9927540, (0 missing)
##       age               < 83.5   to the left,  improve=1.0853600, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.0471420, (0 missing)
##       copd              < 0.5    to the left,  improve=0.9387681, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.5135517, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the right, agree=0.848, adj=0.391, (0 split)
##       age        < 89.5   to the right, agree=0.761, adj=0.043, (0 split)
## 
## Node number 867: 121 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.5619835  P(node) =0.00605
##     class counts:    53    39    22     5     2
##    probabilities: 0.438 0.322 0.182 0.041 0.017 
##   left son=1734 (104 obs) right son=1735 (17 obs)
##   Primary splits:
##       age               < 69.5   to the right, improve=2.7636680, (0 missing)
##       reimbursement2008 < 2675   to the left,  improve=1.1093730, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.9745305, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.9029175, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5339984, (0 missing)
## 
## Node number 872: 133 observations,    complexity param=0.0006084576
##   predicted class=B1  expected loss=0.5263158  P(node) =0.00665
##     class counts:    63    48    11    11     0
##    probabilities: 0.474 0.361 0.083 0.083 0.000 
##   left son=1744 (8 obs) right son=1745 (125 obs)
##   Primary splits:
##       reimbursement2008 < 3365   to the right, improve=1.9610380, (0 missing)
##       age               < 69.5   to the left,  improve=1.5783450, (0 missing)
##       depression        < 0.5    to the left,  improve=1.1410180, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.9988038, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.7504819, (0 missing)
## 
## Node number 873: 13 observations
##   predicted class=B3  expected loss=0.6153846  P(node) =0.00065
##     class counts:     2     4     5     2     0
##    probabilities: 0.154 0.308 0.385 0.154 0.000 
## 
## Node number 874: 11 observations
##   predicted class=B1  expected loss=0.5454545  P(node) =0.00055
##     class counts:     5     2     3     1     0
##    probabilities: 0.455 0.182 0.273 0.091 0.000 
## 
## Node number 875: 56 observations,    complexity param=0.0003549336
##   predicted class=B2  expected loss=0.625  P(node) =0.0028
##     class counts:    13    21    14     8     0
##    probabilities: 0.232 0.375 0.250 0.143 0.000 
##   left son=1750 (10 obs) right son=1751 (46 obs)
##   Primary splits:
##       reimbursement2008 < 2755   to the left,  improve=1.7947200, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6517857, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5812448, (0 missing)
##       age               < 82.5   to the right, improve=0.5119048, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=0.1398924, (0 missing)
## 
## Node number 876: 41 observations
##   predicted class=B2  expected loss=0.3902439  P(node) =0.00205
##     class counts:     9    25     6     1     0
##    probabilities: 0.220 0.610 0.146 0.024 0.000 
## 
## Node number 877: 16 observations
##   predicted class=B1  expected loss=0.5625  P(node) =0.0008
##     class counts:     7     4     3     2     0
##    probabilities: 0.438 0.250 0.188 0.125 0.000 
## 
## Node number 878: 9 observations
##   predicted class=B1  expected loss=0.5555556  P(node) =0.00045
##     class counts:     4     2     3     0     0
##    probabilities: 0.444 0.222 0.333 0.000 0.000 
## 
## Node number 879: 18 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.0009
##     class counts:     0    10     8     0     0
##    probabilities: 0.000 0.556 0.444 0.000 0.000 
## 
## Node number 880: 142 observations,    complexity param=0.0002788764
##   predicted class=B2  expected loss=0.5704225  P(node) =0.0071
##     class counts:    49    61    27     4     1
##    probabilities: 0.345 0.430 0.190 0.028 0.007 
##   left son=1760 (104 obs) right son=1761 (38 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=1.5963530, (0 missing)
##       reimbursement2008 < 2805   to the right, improve=1.3502880, (0 missing)
##       copd              < 0.5    to the left,  improve=1.1429120, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.0117310, (0 missing)
##       age               < 66.5   to the left,  improve=0.9566806, (0 missing)
## 
## Node number 881: 8 observations
##   predicted class=B2  expected loss=0.25  P(node) =0.0004
##     class counts:     1     6     0     1     0
##    probabilities: 0.125 0.750 0.000 0.125 0.000 
## 
## Node number 888: 40 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.575  P(node) =0.002
##     class counts:    17    16     5     1     1
##    probabilities: 0.425 0.400 0.125 0.025 0.025 
##   left son=1776 (11 obs) right son=1777 (29 obs)
##   Primary splits:
##       age               < 82.5   to the right, improve=1.2360500, (0 missing)
##       copd              < 0.5    to the left,  improve=1.0506490, (0 missing)
##       reimbursement2008 < 3215   to the right, improve=0.7666667, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.7606061, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.5901099, (0 missing)
## 
## Node number 889: 30 observations
##   predicted class=B2  expected loss=0.3666667  P(node) =0.0015
##     class counts:     5    19     3     3     0
##    probabilities: 0.167 0.633 0.100 0.100 0.000 
## 
## Node number 896: 26 observations
##   predicted class=B1  expected loss=0.07692308  P(node) =0.0013
##     class counts:    24     1     1     0     0
##    probabilities: 0.923 0.038 0.038 0.000 0.000 
## 
## Node number 897: 94 observations,    complexity param=0.0001014096
##   predicted class=B1  expected loss=0.3297872  P(node) =0.0047
##     class counts:    63    20     7     4     0
##    probabilities: 0.670 0.213 0.074 0.043 0.000 
##   left son=1794 (64 obs) right son=1795 (30 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=1.4985370, (0 missing)
##       age               < 49.5   to the right, improve=1.2949040, (0 missing)
##       reimbursement2008 < 3800   to the left,  improve=1.1582080, (0 missing)
##       copd              < 0.5    to the left,  improve=0.9964539, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.4900436, (0 missing)
##   Surrogate splits:
##       age               < 91.5   to the left,  agree=0.723, adj=0.133, (0 split)
##       stroke            < 0.5    to the left,  agree=0.723, adj=0.133, (0 split)
##       copd              < 0.5    to the left,  agree=0.702, adj=0.067, (0 split)
##       reimbursement2008 < 7705   to the left,  agree=0.691, adj=0.033, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.691, adj=0.033, (0 split)
## 
## Node number 898: 89 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3595506  P(node) =0.00445
##     class counts:    57    21     7     3     1
##    probabilities: 0.640 0.236 0.079 0.034 0.011 
##   left son=1796 (22 obs) right son=1797 (67 obs)
##   Primary splits:
##       reimbursement2008 < 9310   to the left,  improve=2.1396340, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.6199640, (0 missing)
##       copd              < 0.5    to the left,  improve=0.9273400, (0 missing)
##       age               < 59.5   to the right, improve=0.8270218, (0 missing)
##       stroke            < 0.5    to the right, improve=0.8268807, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.865, adj=0.455, (0 split)
##       age        < 94.5   to the right, agree=0.775, adj=0.091, (0 split)
## 
## Node number 899: 121 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.4958678  P(node) =0.00605
##     class counts:    61    35    21     3     1
##    probabilities: 0.504 0.289 0.174 0.025 0.008 
##   left son=1798 (105 obs) right son=1799 (16 obs)
##   Primary splits:
##       reimbursement2008 < 6145   to the left,  improve=3.6574090, (0 missing)
##       age               < 88.5   to the right, improve=1.6732430, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.4740051, (0 missing)
##       kidney            < 0.5    to the right, improve=0.3966942, (0 missing)
##       copd              < 0.5    to the left,  improve=0.2864993, (0 missing)
## 
## Node number 902: 60 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.5  P(node) =0.003
##     class counts:    30    23     5     2     0
##    probabilities: 0.500 0.383 0.083 0.033 0.000 
##   left son=1804 (26 obs) right son=1805 (34 obs)
##   Primary splits:
##       age               < 74.5   to the left,  improve=1.7361990, (0 missing)
##       reimbursement2008 < 9210   to the right, improve=1.6200000, (0 missing)
##       ihd               < 0.5    to the right, improve=1.1258370, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.5012422, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.4916667, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 3905   to the left,  agree=0.667, adj=0.231, (0 split)
##       stroke            < 0.5    to the right, agree=0.600, adj=0.077, (0 split)
## 
## Node number 903: 14 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.0007
##     class counts:     3    10     0     0     1
##    probabilities: 0.214 0.714 0.000 0.000 0.071 
## 
## Node number 906: 16 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0008
##     class counts:     5     8     3     0     0
##    probabilities: 0.312 0.500 0.188 0.000 0.000 
## 
## Node number 907: 15 observations
##   predicted class=B1  expected loss=0.5333333  P(node) =0.00075
##     class counts:     7     3     4     1     0
##    probabilities: 0.467 0.200 0.267 0.067 0.000 
## 
## Node number 910: 18 observations
##   predicted class=B2  expected loss=0.3888889  P(node) =0.0009
##     class counts:     4    11     3     0     0
##    probabilities: 0.222 0.611 0.167 0.000 0.000 
## 
## Node number 911: 54 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.6666667  P(node) =0.0027
##     class counts:    18    18    16     2     0
##    probabilities: 0.333 0.333 0.296 0.037 0.000 
##   left son=1822 (22 obs) right son=1823 (32 obs)
##   Primary splits:
##       reimbursement2008 < 13120  to the right, improve=1.9920030, (0 missing)
##       copd              < 0.5    to the right, improve=1.6851850, (0 missing)
##       kidney            < 0.5    to the right, improve=0.7220273, (0 missing)
##       age               < 81.5   to the right, improve=0.6681397, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.4629630, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.796, adj=0.500, (0 split)
##       age        < 94.5   to the right, agree=0.667, adj=0.182, (0 split)
##       kidney     < 0.5    to the right, agree=0.611, adj=0.045, (0 split)
## 
## Node number 914: 25 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.48  P(node) =0.00125
##     class counts:    13     7     0     5     0
##    probabilities: 0.520 0.280 0.000 0.200 0.000 
##   left son=1828 (18 obs) right son=1829 (7 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=1.3911110, (0 missing)
##       age               < 71.5   to the right, improve=0.7994805, (0 missing)
##       reimbursement2008 < 5140   to the left,  improve=0.6774359, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.3059740, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 5705   to the left,  agree=0.76, adj=0.143, (0 split)
## 
## Node number 915: 7 observations
##   predicted class=B1  expected loss=0.5714286  P(node) =0.00035
##     class counts:     3     1     3     0     0
##    probabilities: 0.429 0.143 0.429 0.000 0.000 
## 
## Node number 936: 27 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4074074  P(node) =0.00135
##     class counts:    16     8     2     1     0
##    probabilities: 0.593 0.296 0.074 0.037 0.000 
##   left son=1872 (11 obs) right son=1873 (16 obs)
##   Primary splits:
##       reimbursement2008 < 14045  to the right, improve=1.6334180, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.3152360, (0 missing)
##       kidney            < 0.5    to the right, improve=0.9629630, (0 missing)
##       age               < 69.5   to the right, improve=0.8518519, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7261209, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.778, adj=0.455, (0 split)
##       age        < 77.5   to the right, agree=0.704, adj=0.273, (0 split)
## 
## Node number 937: 45 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.4222222  P(node) =0.00225
##     class counts:    12    26     5     2     0
##    probabilities: 0.267 0.578 0.111 0.044 0.000 
##   left son=1874 (7 obs) right son=1875 (38 obs)
##   Primary splits:
##       reimbursement2008 < 3740   to the left,  improve=1.5017540, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7257703, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.6939394, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5049550, (0 missing)
##       kidney            < 0.5    to the right, improve=0.4306306, (0 missing)
## 
## Node number 938: 12 observations
##   predicted class=B2  expected loss=0.1666667  P(node) =0.0006
##     class counts:     1    10     1     0     0
##    probabilities: 0.083 0.833 0.083 0.000 0.000 
## 
## Node number 939: 52 observations,    complexity param=0.0003549336
##   predicted class=B2  expected loss=0.5769231  P(node) =0.0026
##     class counts:    11    22    15     4     0
##    probabilities: 0.212 0.423 0.288 0.077 0.000 
##   left son=1878 (13 obs) right son=1879 (39 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=2.0897440, (0 missing)
##       age               < 79.5   to the right, improve=1.0514040, (0 missing)
##       reimbursement2008 < 5860   to the right, improve=1.0026590, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.9019404, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.6196581, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 3925   to the left,  agree=0.769, adj=0.077, (0 split)
## 
## Node number 940: 13 observations
##   predicted class=B1  expected loss=0.2307692  P(node) =0.00065
##     class counts:    10     2     1     0     0
##    probabilities: 0.769 0.154 0.077 0.000 0.000 
## 
## Node number 941: 33 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.6363636  P(node) =0.00165
##     class counts:    12     7     9     5     0
##    probabilities: 0.364 0.212 0.273 0.152 0.000 
##   left son=1882 (26 obs) right son=1883 (7 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=1.4778550, (0 missing)
##       reimbursement2008 < 10080  to the left,  improve=1.4293940, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.9393939, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7727273, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7575758, (0 missing)
## 
## Node number 956: 41 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.6097561  P(node) =0.00205
##     class counts:    11    16    10     4     0
##    probabilities: 0.268 0.390 0.244 0.098 0.000 
##   left son=1912 (30 obs) right son=1913 (11 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=1.8119730, (0 missing)
##       reimbursement2008 < 5410   to the left,  improve=1.1877310, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.8998522, (0 missing)
##       age               < 70.5   to the right, improve=0.8138451, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.7968658, (0 missing)
##   Surrogate splits:
##       age    < 37     to the right, agree=0.756, adj=0.091, (0 split)
##       stroke < 0.5    to the left,  agree=0.756, adj=0.091, (0 split)
## 
## Node number 957: 38 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.5  P(node) =0.0019
##     class counts:     4    19    13     2     0
##    probabilities: 0.105 0.500 0.342 0.053 0.000 
##   left son=1914 (31 obs) right son=1915 (7 obs)
##   Primary splits:
##       reimbursement2008 < 4300   to the right, improve=2.3189430, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.0000000, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.9492850, (0 missing)
##       age               < 81.5   to the left,  improve=0.7535885, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.6058612, (0 missing)
##   Surrogate splits:
##       age < 92.5   to the left,  agree=0.842, adj=0.143, (0 split)
## 
## Node number 960: 155 observations,    complexity param=0.0003422574
##   predicted class=B1  expected loss=0.5032258  P(node) =0.00775
##     class counts:    77    47    28     3     0
##    probabilities: 0.497 0.303 0.181 0.019 0.000 
##   left son=1920 (32 obs) right son=1921 (123 obs)
##   Primary splits:
##       reimbursement2008 < 6290   to the right, improve=1.7144870, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.3927660, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.5998232, (0 missing)
##       age               < 66.5   to the left,  improve=0.5282028, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.2484000, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.852, adj=0.281, (0 split)
## 
## Node number 961: 44 observations
##   predicted class=B2  expected loss=0.4318182  P(node) =0.0022
##     class counts:    13    25     4     2     0
##    probabilities: 0.295 0.568 0.091 0.045 0.000 
## 
## Node number 962: 52 observations,    complexity param=0.000507048
##   predicted class=B1  expected loss=0.6923077  P(node) =0.0026
##     class counts:    16    16     9    10     1
##    probabilities: 0.308 0.308 0.173 0.192 0.019 
##   left son=1924 (31 obs) right son=1925 (21 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=1.6461660, (0 missing)
##       age               < 52     to the right, improve=1.5856640, (0 missing)
##       reimbursement2008 < 13440  to the right, improve=1.1403330, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.9728254, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7932401, (0 missing)
##   Surrogate splits:
##       age               < 50.5   to the right, agree=0.654, adj=0.143, (0 split)
##       stroke            < 0.5    to the left,  agree=0.654, adj=0.143, (0 split)
##       depression        < 0.5    to the left,  agree=0.635, adj=0.095, (0 split)
##       reimbursement2008 < 16130  to the left,  agree=0.615, adj=0.048, (0 split)
## 
## Node number 963: 26 observations,    complexity param=0.0001521144
##   predicted class=B3  expected loss=0.5769231  P(node) =0.0013
##     class counts:     8     3    11     4     0
##    probabilities: 0.308 0.115 0.423 0.154 0.000 
##   left son=1926 (15 obs) right son=1927 (11 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=1.1109560, (0 missing)
##       reimbursement2008 < 10135  to the right, improve=0.9468864, (0 missing)
##       age               < 65     to the right, improve=0.5480769, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5064103, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.4720965, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 9215   to the right, agree=0.692, adj=0.273, (0 split)
##       age               < 68.5   to the left,  agree=0.654, adj=0.182, (0 split)
##       stroke            < 0.5    to the left,  agree=0.654, adj=0.182, (0 split)
##       ihd               < 0.5    to the right, agree=0.615, adj=0.091, (0 split)
## 
## Node number 964: 170 observations,    complexity param=0.0004563432
##   predicted class=B1  expected loss=0.5411765  P(node) =0.0085
##     class counts:    78    58    23    10     1
##    probabilities: 0.459 0.341 0.135 0.059 0.006 
##   left son=1928 (144 obs) right son=1929 (26 obs)
##   Primary splits:
##       age               < 88.5   to the left,  improve=2.0616640, (0 missing)
##       reimbursement2008 < 5215   to the left,  improve=1.6700280, (0 missing)
##       copd              < 0.5    to the right, improve=0.6860574, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6145002, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.5698065, (0 missing)
## 
## Node number 965: 157 observations,    complexity param=0.0008746577
##   predicted class=B2  expected loss=0.5732484  P(node) =0.00785
##     class counts:    49    67    27    12     2
##    probabilities: 0.312 0.427 0.172 0.076 0.013 
##   left son=1930 (28 obs) right son=1931 (129 obs)
##   Primary splits:
##       age        < 88.5   to the right, improve=2.733535, (0 missing)
##       copd       < 0.5    to the left,  improve=2.275853, (0 missing)
##       alzheimers < 0.5    to the left,  improve=1.745083, (0 missing)
##       ihd        < 0.5    to the left,  improve=1.711287, (0 missing)
##       stroke     < 0.5    to the left,  improve=1.709726, (0 missing)
## 
## Node number 966: 74 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.3513514  P(node) =0.0037
##     class counts:    17    48     7     2     0
##    probabilities: 0.230 0.649 0.095 0.027 0.000 
##   left son=1932 (64 obs) right son=1933 (10 obs)
##   Primary splits:
##       reimbursement2008 < 4725   to the left,  improve=2.1494930, (0 missing)
##       age               < 72.5   to the left,  improve=1.9802800, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.4229040, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5439425, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3682432, (0 missing)
## 
## Node number 967: 113 observations,    complexity param=0.000380286
##   predicted class=B2  expected loss=0.5221239  P(node) =0.00565
##     class counts:    34    54    20     5     0
##    probabilities: 0.301 0.478 0.177 0.044 0.000 
##   left son=1934 (9 obs) right son=1935 (104 obs)
##   Primary splits:
##       age               < 78.5   to the left,  improve=2.662942, (0 missing)
##       depression        < 0.5    to the right, improve=2.539583, (0 missing)
##       stroke            < 0.5    to the right, improve=1.321986, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.244120, (0 missing)
##       reimbursement2008 < 4030   to the left,  improve=0.939590, (0 missing)
## 
## Node number 972: 8 observations
##   predicted class=B2  expected loss=0.125  P(node) =0.0004
##     class counts:     1     7     0     0     0
##    probabilities: 0.125 0.875 0.000 0.000 0.000 
## 
## Node number 973: 112 observations,    complexity param=0.0005324004
##   predicted class=B2  expected loss=0.6517857  P(node) =0.0056
##     class counts:    24    39    38    11     0
##    probabilities: 0.214 0.348 0.339 0.098 0.000 
##   left son=1946 (49 obs) right son=1947 (63 obs)
##   Primary splits:
##       age               < 71.5   to the left,  improve=1.734410, (0 missing)
##       reimbursement2008 < 6810   to the left,  improve=1.588784, (0 missing)
##       depression        < 0.5    to the left,  improve=1.542396, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.169209, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.109144, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 24415  to the right, agree=0.58, adj=0.041, (0 split)
## 
## Node number 984: 56 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.625  P(node) =0.0028
##     class counts:    21    20     6     6     3
##    probabilities: 0.375 0.357 0.107 0.107 0.054 
##   left son=1968 (38 obs) right son=1969 (18 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.4889310, (0 missing)
##       age               < 68.5   to the right, improve=2.0304350, (0 missing)
##       reimbursement2008 < 14115  to the left,  improve=1.8107140, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=0.9375588, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5983261, (0 missing)
##   Surrogate splits:
##       age               < 57     to the right, agree=0.714, adj=0.111, (0 split)
##       reimbursement2008 < 60180  to the left,  agree=0.714, adj=0.111, (0 split)
##       bucket2008        < 4.5    to the left,  agree=0.714, adj=0.111, (0 split)
## 
## Node number 985: 127 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.519685  P(node) =0.00635
##     class counts:    31    61    17    17     1
##    probabilities: 0.244 0.480 0.134 0.134 0.008 
##   left son=1970 (85 obs) right son=1971 (42 obs)
##   Primary splits:
##       reimbursement2008 < 6240   to the left,  improve=2.0896490, (0 missing)
##       age               < 67.5   to the left,  improve=1.6822110, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.2999880, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.1106320, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.8561487, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.803, adj=0.405, (0 split)
##       cancer     < 0.5    to the left,  agree=0.685, adj=0.048, (0 split)
## 
## Node number 986: 37 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5945946  P(node) =0.00185
##     class counts:    10    15     5     7     0
##    probabilities: 0.270 0.405 0.135 0.189 0.000 
##   left son=1972 (16 obs) right son=1973 (21 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=1.7162160, (0 missing)
##       age               < 84.5   to the right, improve=1.4384380, (0 missing)
##       copd              < 0.5    to the right, improve=1.2456280, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.0857810, (0 missing)
##       reimbursement2008 < 6875   to the right, improve=0.7102638, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 7200   to the left,  agree=0.703, adj=0.313, (0 split)
##       ihd               < 0.5    to the left,  agree=0.649, adj=0.188, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.649, adj=0.188, (0 split)
##       copd              < 0.5    to the left,  agree=0.595, adj=0.063, (0 split)
## 
## Node number 987: 62 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4032258  P(node) =0.0031
##     class counts:     6    37    16     3     0
##    probabilities: 0.097 0.597 0.258 0.048 0.000 
##   left son=1974 (17 obs) right son=1975 (45 obs)
##   Primary splits:
##       reimbursement2008 < 9010   to the right, improve=1.1586340, (0 missing)
##       age               < 64.5   to the right, improve=0.9974302, (0 missing)
##       cancer            < 0.5    to the right, improve=0.9645161, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5071025, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4342640, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.919, adj=0.706, (0 split)
## 
## Node number 988: 16 observations
##   predicted class=B2  expected loss=0.3125  P(node) =0.0008
##     class counts:     3    11     2     0     0
##    probabilities: 0.188 0.688 0.125 0.000 0.000 
## 
## Node number 989: 225 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.56  P(node) =0.01125
##     class counts:    43    99    60    21     2
##    probabilities: 0.191 0.440 0.267 0.093 0.009 
##   left son=1978 (216 obs) right son=1979 (9 obs)
##   Primary splits:
##       reimbursement2008 < 39120  to the left,  improve=1.9111110, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.5225480, (0 missing)
##       age               < 71.5   to the right, improve=0.9369227, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.9367521, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.7079276, (0 missing)
##   Surrogate splits:
##       bucket2008 < 4.5    to the left,  agree=0.969, adj=0.222, (0 split)
## 
## Node number 992: 67 observations,    complexity param=0.000507048
##   predicted class=B1  expected loss=0.6716418  P(node) =0.00335
##     class counts:    22    18    21     4     2
##    probabilities: 0.328 0.269 0.313 0.060 0.030 
##   left son=1984 (43 obs) right son=1985 (24 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=1.596523, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.434701, (0 missing)
##       reimbursement2008 < 8080   to the left,  improve=1.256193, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.048920, (0 missing)
##       age               < 96.5   to the left,  improve=1.002126, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.672, adj=0.083, (0 split)
##       ihd    < 0.5    to the right, agree=0.657, adj=0.042, (0 split)
## 
## Node number 993: 279 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6344086  P(node) =0.01395
##     class counts:    66   102    50    53     8
##    probabilities: 0.237 0.366 0.179 0.190 0.029 
##   left son=1986 (11 obs) right son=1987 (268 obs)
##   Primary splits:
##       reimbursement2008 < 6780   to the left,  improve=2.133825, (0 missing)
##       age               < 77.5   to the left,  improve=1.516129, (0 missing)
##       stroke            < 0.5    to the right, improve=1.276040, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.116912, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.035800, (0 missing)
## 
## Node number 994: 19 observations
##   predicted class=B2  expected loss=0.2631579  P(node) =0.00095
##     class counts:     3    14     1     1     0
##    probabilities: 0.158 0.737 0.053 0.053 0.000 
## 
## Node number 995: 247 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6153846  P(node) =0.01235
##     class counts:    47    95    67    32     6
##    probabilities: 0.190 0.385 0.271 0.130 0.024 
##   left son=1990 (235 obs) right son=1991 (12 obs)
##   Primary splits:
##       age               < 88.5   to the left,  improve=2.7973120, (0 missing)
##       reimbursement2008 < 6170   to the left,  improve=2.4372470, (0 missing)
##       depression        < 0.5    to the right, improve=0.9399906, (0 missing)
##       ihd               < 0.5    to the right, improve=0.8524106, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.7164122, (0 missing)
## 
## Node number 1002: 107 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.3925234  P(node) =0.00535
##     class counts:    16    65    15    10     1
##    probabilities: 0.150 0.607 0.140 0.093 0.009 
##   left son=2004 (88 obs) right son=2005 (19 obs)
##   Primary splits:
##       reimbursement2008 < 4595   to the left,  improve=1.5568240, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7322522, (0 missing)
##       copd              < 0.5    to the right, improve=0.6210399, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.6176956, (0 missing)
##       age               < 81.5   to the right, improve=0.4955512, (0 missing)
## 
## Node number 1003: 25 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.6  P(node) =0.00125
##     class counts:     4    10     7     4     0
##    probabilities: 0.160 0.400 0.280 0.160 0.000 
##   left son=2006 (16 obs) right son=2007 (9 obs)
##   Primary splits:
##       reimbursement2008 < 4975   to the right, improve=0.9127778, (0 missing)
##       depression        < 0.5    to the left,  improve=0.8119481, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5100000, (0 missing)
##       age               < 66.5   to the right, improve=0.3473016, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.2933333, (0 missing)
##   Surrogate splits:
##       age    < 62.5   to the right, agree=0.80, adj=0.444, (0 split)
##       stroke < 0.5    to the left,  agree=0.68, adj=0.111, (0 split)
## 
## Node number 1004: 16 observations
##   predicted class=B1  expected loss=0.625  P(node) =0.0008
##     class counts:     6     5     3     2     0
##    probabilities: 0.375 0.312 0.188 0.125 0.000 
## 
## Node number 1005: 8 observations
##   predicted class=B3  expected loss=0.375  P(node) =0.0004
##     class counts:     1     2     5     0     0
##    probabilities: 0.125 0.250 0.625 0.000 0.000 
## 
## Node number 1006: 253 observations,    complexity param=0.0002028192
##   predicted class=B2  expected loss=0.5454545  P(node) =0.01265
##     class counts:    29   115    69    35     5
##    probabilities: 0.115 0.455 0.273 0.138 0.020 
##   left son=2012 (35 obs) right son=2013 (218 obs)
##   Primary splits:
##       reimbursement2008 < 6565   to the left,  improve=1.3116340, (0 missing)
##       copd              < 0.5    to the left,  improve=1.0918940, (0 missing)
##       age               < 39     to the left,  improve=0.9539227, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8542281, (0 missing)
##       cancer            < 0.5    to the right, improve=0.8037400, (0 missing)
## 
## Node number 1007: 32 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.375  P(node) =0.0016
##     class counts:     0    20     8     3     1
##    probabilities: 0.000 0.625 0.250 0.094 0.031 
##   left son=2014 (22 obs) right son=2015 (10 obs)
##   Primary splits:
##       reimbursement2008 < 5385   to the right, improve=2.4965910, (0 missing)
##       depression        < 0.5    to the right, improve=1.5511360, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.7271825, (0 missing)
##       age               < 85     to the right, improve=0.5208333, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3541667, (0 missing)
##   Surrogate splits:
##       age < 90.5   to the left,  agree=0.75, adj=0.2, (0 split)
## 
## Node number 1012: 13 observations
##   predicted class=B2  expected loss=0.1538462  P(node) =0.00065
##     class counts:     1    11     0     0     1
##    probabilities: 0.077 0.846 0.000 0.000 0.077 
## 
## Node number 1013: 7 observations
##   predicted class=B4  expected loss=0.4285714  P(node) =0.00035
##     class counts:     0     1     2     4     0
##    probabilities: 0.000 0.143 0.286 0.571 0.000 
## 
## Node number 1016: 95 observations,    complexity param=0.000507048
##   predicted class=B1  expected loss=0.7157895  P(node) =0.00475
##     class counts:    27    23    20    25     0
##    probabilities: 0.284 0.242 0.211 0.263 0.000 
##   left son=2032 (67 obs) right son=2033 (28 obs)
##   Primary splits:
##       reimbursement2008 < 18065  to the right, improve=1.9044550, (0 missing)
##       age               < 86.5   to the left,  improve=1.6124630, (0 missing)
##       bucket2008        < 3.5    to the right, improve=0.8617544, (0 missing)
##       cancer            < 0.5    to the right, improve=0.8550877, (0 missing)
##       stroke            < 0.5    to the right, improve=0.5227689, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.821, adj=0.393, (0 split)
## 
## Node number 1017: 138 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6376812  P(node) =0.0069
##     class counts:    21    50    29    30     8
##    probabilities: 0.152 0.362 0.210 0.217 0.058 
##   left son=2034 (41 obs) right son=2035 (97 obs)
##   Primary splits:
##       reimbursement2008 < 22770  to the right, improve=2.1050500, (0 missing)
##       age               < 73.5   to the left,  improve=1.6683600, (0 missing)
##       stroke            < 0.5    to the right, improve=1.3740260, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.3465420, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9647403, (0 missing)
##   Surrogate splits:
##       age < 40.5   to the left,  agree=0.717, adj=0.049, (0 split)
## 
## Node number 1018: 140 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.5928571  P(node) =0.007
##     class counts:    17    57    38    20     8
##    probabilities: 0.121 0.407 0.271 0.143 0.057 
##   left son=2036 (125 obs) right son=2037 (15 obs)
##   Primary splits:
##       age               < 65     to the right, improve=1.6013330, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.3095240, (0 missing)
##       reimbursement2008 < 16720  to the right, improve=1.2510020, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9871662, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9854436, (0 missing)
## 
## Node number 1019: 23 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.4782609  P(node) =0.00115
##     class counts:     1     5    12     4     1
##    probabilities: 0.043 0.217 0.522 0.174 0.043 
##   left son=2038 (13 obs) right son=2039 (10 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=3.5311040, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.4604740, (0 missing)
##       age               < 79     to the left,  improve=1.2028990, (0 missing)
##       reimbursement2008 < 20175  to the left,  improve=0.3003344, (0 missing)
##       depression        < 0.5    to the right, improve=0.1271410, (0 missing)
##   Surrogate splits:
##       age               < 83.5   to the left,  agree=0.652, adj=0.2, (0 split)
##       cancer            < 0.5    to the left,  agree=0.652, adj=0.2, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.652, adj=0.2, (0 split)
##       reimbursement2008 < 17675  to the left,  agree=0.609, adj=0.1, (0 split)
## 
## Node number 1022: 91 observations,    complexity param=0.0002662002
##   predicted class=B2  expected loss=0.5164835  P(node) =0.00455
##     class counts:     6    44    17    21     3
##    probabilities: 0.066 0.484 0.187 0.231 0.033 
##   left son=2044 (47 obs) right son=2045 (44 obs)
##   Primary splits:
##       age               < 72     to the right, improve=1.4196230, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.2187220, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9937374, (0 missing)
##       stroke            < 0.5    to the right, improve=0.7373929, (0 missing)
##       reimbursement2008 < 31655  to the right, improve=0.7326007, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 27945  to the left,  agree=0.604, adj=0.182, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.582, adj=0.136, (0 split)
##       copd              < 0.5    to the left,  agree=0.571, adj=0.114, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.560, adj=0.091, (0 split)
##       arthritis         < 0.5    to the left,  agree=0.549, adj=0.068, (0 split)
## 
## Node number 1023: 331 observations,    complexity param=0.000507048
##   predicted class=B4  expected loss=0.6827795  P(node) =0.01655
##     class counts:    24   104    80   105    18
##    probabilities: 0.073 0.314 0.242 0.317 0.054 
##   left son=2046 (97 obs) right son=2047 (234 obs)
##   Primary splits:
##       stroke            < 0.5    to the right, improve=1.835692, (0 missing)
##       age               < 34.5   to the left,  improve=1.722335, (0 missing)
##       reimbursement2008 < 52775  to the right, improve=1.679153, (0 missing)
##       bucket2008        < 4.5    to the right, improve=1.290835, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.283171, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 92615  to the right, agree=0.713, adj=0.021, (0 split)
## 
## Node number 1284: 94 observations
##   predicted class=B1  expected loss=0.106383  P(node) =0.0047
##     class counts:    84     5     4     1     0
##    probabilities: 0.894 0.053 0.043 0.011 0.000 
## 
## Node number 1285: 707 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.165488  P(node) =0.03535
##     class counts:   590    68    36    11     2
##    probabilities: 0.835 0.096 0.051 0.016 0.003 
##   left son=2570 (277 obs) right son=2571 (430 obs)
##   Primary splits:
##       reimbursement2008 < 495    to the right, improve=0.7004222, (0 missing)
##       age               < 83.5   to the right, improve=0.4988776, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.3588292, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.3154163, (0 missing)
##       depression        < 0.5    to the left,  improve=0.3116005, (0 missing)
##   Surrogate splits:
##       heart.failure < 0.5    to the right, agree=0.611, adj=0.007, (0 split)
##       ihd           < 0.5    to the right, agree=0.610, adj=0.004, (0 split)
## 
## Node number 1414: 43 observations
##   predicted class=B1  expected loss=0.2790698  P(node) =0.00215
##     class counts:    31     6     3     3     0
##    probabilities: 0.721 0.140 0.070 0.070 0.000 
## 
## Node number 1415: 14 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0007
##     class counts:     5     7     0     2     0
##    probabilities: 0.357 0.500 0.000 0.143 0.000 
## 
## Node number 1420: 9 observations
##   predicted class=B1  expected loss=0.1111111  P(node) =0.00045
##     class counts:     8     0     0     1     0
##    probabilities: 0.889 0.000 0.000 0.111 0.000 
## 
## Node number 1421: 67 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2985075  P(node) =0.00335
##     class counts:    47    16     3     1     0
##    probabilities: 0.701 0.239 0.045 0.015 0.000 
##   left son=2842 (60 obs) right son=2843 (7 obs)
##   Primary splits:
##       age               < 78.5   to the left,  improve=1.4644630, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.8523372, (0 missing)
##       kidney            < 0.5    to the right, improve=0.4113964, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.3161117, (0 missing)
##       reimbursement2008 < 775    to the right, improve=0.2780923, (0 missing)
## 
## Node number 1440: 27 observations
##   predicted class=B1  expected loss=0.07407407  P(node) =0.00135
##     class counts:    25     1     1     0     0
##    probabilities: 0.926 0.037 0.037 0.000 0.000 
## 
## Node number 1441: 256 observations,    complexity param=5.07048e-05
##   predicted class=B1  expected loss=0.2265625  P(node) =0.0128
##     class counts:   198    28    21     9     0
##    probabilities: 0.773 0.109 0.082 0.035 0.000 
##   left son=2882 (197 obs) right son=2883 (59 obs)
##   Primary splits:
##       age               < 80.5   to the left,  improve=1.4661490, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.7479467, (0 missing)
##       reimbursement2008 < 1315   to the right, improve=0.5371438, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4432897, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.3477601, (0 missing)
## 
## Node number 1442: 158 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.2721519  P(node) =0.0079
##     class counts:   115    25    13     5     0
##    probabilities: 0.728 0.158 0.082 0.032 0.000 
##   left son=2884 (109 obs) right son=2885 (49 obs)
##   Primary splits:
##       age               < 73.5   to the right, improve=0.6469703, (0 missing)
##       reimbursement2008 < 1375   to the right, improve=0.4601807, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.3961186, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3805342, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.3789804, (0 missing)
## 
## Node number 1443: 8 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0004
##     class counts:     4     3     1     0     0
##    probabilities: 0.500 0.375 0.125 0.000 0.000 
## 
## Node number 1446: 52 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2884615  P(node) =0.0026
##     class counts:    37    10     2     3     0
##    probabilities: 0.712 0.192 0.038 0.058 0.000 
##   left son=2892 (32 obs) right son=2893 (20 obs)
##   Primary splits:
##       reimbursement2008 < 1155   to the right, improve=1.2875000, (0 missing)
##       age               < 65.5   to the right, improve=0.9991597, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.8375000, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6047619, (0 missing)
##       depression        < 0.5    to the right, improve=0.2711712, (0 missing)
##   Surrogate splits:
##       diabetes   < 0.5    to the left,  agree=0.692, adj=0.20, (0 split)
##       copd       < 0.5    to the left,  agree=0.654, adj=0.10, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.635, adj=0.05, (0 split)
## 
## Node number 1447: 35 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.4285714  P(node) =0.00175
##     class counts:    20    14     1     0     0
##    probabilities: 0.571 0.400 0.029 0.000 0.000 
##   left son=2894 (15 obs) right son=2895 (20 obs)
##   Primary splits:
##       diabetes      < 0.5    to the right, improve=1.7761900, (0 missing)
##       age           < 47.5   to the right, improve=1.5857140, (0 missing)
##       heart.failure < 0.5    to the right, improve=0.5724868, (0 missing)
##       depression    < 0.5    to the left,  improve=0.2257519, (0 missing)
##       alzheimers    < 0.5    to the left,  improve=0.1650794, (0 missing)
##   Surrogate splits:
##       arthritis < 0.5    to the right, agree=0.629, adj=0.133, (0 split)
##       age       < 53.5   to the left,  agree=0.600, adj=0.067, (0 split)
## 
## Node number 1450: 88 observations
##   predicted class=B1  expected loss=0.2954545  P(node) =0.0044
##     class counts:    62    17     5     3     1
##    probabilities: 0.705 0.193 0.057 0.034 0.011 
## 
## Node number 1451: 11 observations
##   predicted class=B2  expected loss=0.4545455  P(node) =0.00055
##     class counts:     3     6     2     0     0
##    probabilities: 0.273 0.545 0.182 0.000 0.000 
## 
## Node number 1474: 145 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.2827586  P(node) =0.00725
##     class counts:   104    25    13     3     0
##    probabilities: 0.717 0.172 0.090 0.021 0.000 
##   left son=2948 (8 obs) right son=2949 (137 obs)
##   Primary splits:
##       age               < 51     to the left,  improve=1.0003520, (0 missing)
##       copd              < 0.5    to the right, improve=0.9153314, (0 missing)
##       reimbursement2008 < 855    to the left,  improve=0.8689655, (0 missing)
##       depression        < 0.5    to the right, improve=0.5758972, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.1184309, (0 missing)
## 
## Node number 1475: 28 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.5357143  P(node) =0.0014
##     class counts:    13     9     4     2     0
##    probabilities: 0.464 0.321 0.143 0.071 0.000 
##   left son=2950 (8 obs) right son=2951 (20 obs)
##   Primary splits:
##       age               < 78.5   to the right, improve=1.607143, (0 missing)
##       reimbursement2008 < 795    to the left,  improve=1.046032, (0 missing)
## 
## Node number 1512: 74 observations
##   predicted class=B1  expected loss=0.2297297  P(node) =0.0037
##     class counts:    57     9     5     3     0
##    probabilities: 0.770 0.122 0.068 0.041 0.000 
## 
## Node number 1513: 139 observations,    complexity param=6.084576e-05
##   predicted class=B1  expected loss=0.3165468  P(node) =0.00695
##     class counts:    95    31    12     0     1
##    probabilities: 0.683 0.223 0.086 0.000 0.007 
##   left son=3026 (14 obs) right son=3027 (125 obs)
##   Primary splits:
##       reimbursement2008 < 1105   to the right, improve=1.4099650, (0 missing)
##       age               < 50.5   to the left,  improve=1.1605620, (0 missing)
##       kidney            < 0.5    to the right, improve=0.6624468, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5567975, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.3267556, (0 missing)
##   Surrogate splits:
##       age < 48     to the left,  agree=0.906, adj=0.071, (0 split)
## 
## Node number 1514: 68 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3382353  P(node) =0.0034
##     class counts:    45    13     5     5     0
##    probabilities: 0.662 0.191 0.074 0.074 0.000 
##   left son=3028 (9 obs) right son=3029 (59 obs)
##   Primary splits:
##       kidney            < 0.5    to the right, improve=1.9792840, (0 missing)
##       reimbursement2008 < 755    to the left,  improve=1.0972640, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.6166667, (0 missing)
##       age               < 67.5   to the left,  improve=0.4893617, (0 missing)
##       depression        < 0.5    to the right, improve=0.4750000, (0 missing)
## 
## Node number 1515: 29 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.5172414  P(node) =0.00145
##     class counts:    14    12     2     1     0
##    probabilities: 0.483 0.414 0.069 0.034 0.000 
##   left son=3030 (20 obs) right son=3031 (9 obs)
##   Primary splits:
##       age               < 83.5   to the right, improve=0.59233720, (0 missing)
##       reimbursement2008 < 805    to the right, improve=0.35900380, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.34587250, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.04029038, (0 missing)
## 
## Node number 1522: 54 observations
##   predicted class=B1  expected loss=0.3703704  P(node) =0.0027
##     class counts:    34    10     6     4     0
##    probabilities: 0.630 0.185 0.111 0.074 0.000 
## 
## Node number 1523: 56 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5535714  P(node) =0.0028
##     class counts:    25    18    11     2     0
##    probabilities: 0.446 0.321 0.196 0.036 0.000 
##   left son=3046 (31 obs) right son=3047 (25 obs)
##   Primary splits:
##       age               < 76.5   to the right, improve=2.6201380, (0 missing)
##       reimbursement2008 < 1225   to the right, improve=1.6819490, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.7819029, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.4322883, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.3928571, (0 missing)
##   Surrogate splits:
##       heart.failure     < 0.5    to the left,  agree=0.714, adj=0.36, (0 split)
##       reimbursement2008 < 1235   to the left,  agree=0.625, adj=0.16, (0 split)
##       kidney            < 0.5    to the left,  agree=0.571, adj=0.04, (0 split)
## 
## Node number 1536: 47 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.2340426  P(node) =0.00235
##     class counts:    36     3     8     0     0
##    probabilities: 0.766 0.064 0.170 0.000 0.000 
##   left son=3072 (40 obs) right son=3073 (7 obs)
##   Primary splits:
##       reimbursement2008 < 1655   to the right, improve=2.2937690, (0 missing)
##       age               < 74.5   to the right, improve=0.9731469, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.5429287, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2009119, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.2009119, (0 missing)
## 
## Node number 1537: 241 observations
##   predicted class=B1  expected loss=0.2821577  P(node) =0.01205
##     class counts:   173    40    20     8     0
##    probabilities: 0.718 0.166 0.083 0.033 0.000 
## 
## Node number 1538: 92 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3369565  P(node) =0.0046
##     class counts:    61    22     7     1     1
##    probabilities: 0.663 0.239 0.076 0.011 0.011 
##   left son=3076 (23 obs) right son=3077 (69 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=0.8695652, (0 missing)
##       reimbursement2008 < 2050   to the right, improve=0.8034579, (0 missing)
##       age               < 48.5   to the right, improve=0.5224638, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2776586, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.2576490, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2545   to the right, agree=0.783, adj=0.13, (0 split)
## 
## Node number 1539: 15 observations
##   predicted class=B1  expected loss=0.6  P(node) =0.00075
##     class counts:     6     5     4     0     0
##    probabilities: 0.400 0.333 0.267 0.000 0.000 
## 
## Node number 1542: 72 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.4027778  P(node) =0.0036
##     class counts:    43    21     6     2     0
##    probabilities: 0.597 0.292 0.083 0.028 0.000 
##   left son=3084 (58 obs) right son=3085 (14 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=1.1709090, (0 missing)
##       reimbursement2008 < 2415   to the left,  improve=1.1055560, (0 missing)
##       age               < 77.5   to the right, improve=0.5181735, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2448002, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.1190754, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2535   to the left,  agree=0.833, adj=0.143, (0 split)
## 
## Node number 1543: 28 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.6071429  P(node) =0.0014
##     class counts:    11     7     5     5     0
##    probabilities: 0.393 0.250 0.179 0.179 0.000 
##   left son=3086 (7 obs) right son=3087 (21 obs)
##   Primary splits:
##       arthritis         < 0.5    to the right, improve=1.3809520, (0 missing)
##       reimbursement2008 < 2070   to the left,  improve=1.1172160, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8539683, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.6925647, (0 missing)
##       age               < 84.5   to the right, improve=0.4345238, (0 missing)
##   Surrogate splits:
##       age < 82.5   to the left,  agree=0.786, adj=0.143, (0 split)
## 
## Node number 1556: 41 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.4146341  P(node) =0.00205
##     class counts:    24    17     0     0     0
##    probabilities: 0.585 0.415 0.000 0.000 0.000 
##   left son=3112 (30 obs) right son=3113 (11 obs)
##   Primary splits:
##       reimbursement2008 < 2765   to the right, improve=1.4781970, (0 missing)
##       age               < 77.5   to the left,  improve=1.4649390, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.4224390, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.5474390, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4579946, (0 missing)
## 
## Node number 1557: 25 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.4  P(node) =0.00125
##     class counts:    15     6     3     0     1
##    probabilities: 0.600 0.240 0.120 0.000 0.040 
##   left son=3114 (18 obs) right son=3115 (7 obs)
##   Primary splits:
##       reimbursement2008 < 3090   to the left,  improve=2.2711110, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=2.0933330, (0 missing)
##       age               < 89.5   to the left,  improve=0.4139683, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.3405556, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.88, adj=0.571, (0 split)
##       diabetes   < 0.5    to the left,  agree=0.80, adj=0.286, (0 split)
##       age        < 93.5   to the left,  agree=0.76, adj=0.143, (0 split)
## 
## Node number 1580: 26 observations
##   predicted class=B1  expected loss=0.3461538  P(node) =0.0013
##     class counts:    17     7     1     0     1
##    probabilities: 0.654 0.269 0.038 0.000 0.038 
## 
## Node number 1581: 24 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.5833333  P(node) =0.0012
##     class counts:    10     9     1     4     0
##    probabilities: 0.417 0.375 0.042 0.167 0.000 
##   left son=3162 (17 obs) right son=3163 (7 obs)
##   Primary splits:
##       age               < 68.5   to the left,  improve=1.2794120, (0 missing)
##       reimbursement2008 < 1855   to the right, improve=1.1785710, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4054622, (0 missing)
## 
## Node number 1590: 113 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5486726  P(node) =0.00565
##     class counts:    51    37    21     3     1
##    probabilities: 0.451 0.327 0.186 0.027 0.009 
##   left son=3180 (8 obs) right son=3181 (105 obs)
##   Primary splits:
##       reimbursement2008 < 3055   to the right, improve=2.8499160, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.9081570, (0 missing)
##       arthritis         < 0.5    to the right, improve=1.0615610, (0 missing)
##       age               < 75.5   to the right, improve=1.0498240, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7734827, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the right, agree=0.991, adj=0.875, (0 split)
## 
## Node number 1591: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     1     5     2     0     0
##    probabilities: 0.125 0.625 0.250 0.000 0.000 
## 
## Node number 1666: 86 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.3604651  P(node) =0.0043
##     class counts:    55    19     7     4     1
##    probabilities: 0.640 0.221 0.081 0.047 0.012 
##   left son=3332 (70 obs) right son=3333 (16 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=2.3426080, (0 missing)
##       age               < 91.5   to the right, improve=1.6553370, (0 missing)
##       copd              < 0.5    to the left,  improve=1.0437260, (0 missing)
##       reimbursement2008 < 2295   to the left,  improve=1.0350680, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4926252, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1585   to the right, agree=0.849, adj=0.187, (0 split)
## 
## Node number 1667: 58 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.5  P(node) =0.0029
##     class counts:    29    24     3     2     0
##    probabilities: 0.500 0.414 0.052 0.034 0.000 
##   left son=3334 (8 obs) right son=3335 (50 obs)
##   Primary splits:
##       age               < 75.5   to the left,  improve=1.4148280, (0 missing)
##       reimbursement2008 < 2375   to the left,  improve=0.6389452, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3897888, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.3122694, (0 missing)
##       copd              < 0.5    to the left,  improve=0.2848276, (0 missing)
## 
## Node number 1670: 63 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.5079365  P(node) =0.00315
##     class counts:    31    27     4     0     1
##    probabilities: 0.492 0.429 0.063 0.000 0.016 
##   left son=3340 (33 obs) right son=3341 (30 obs)
##   Primary splits:
##       reimbursement2008 < 2015   to the left,  improve=1.6441560, (0 missing)
##       age               < 87.5   to the left,  improve=1.0505420, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5047619, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3234222, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.1904762, (0 missing)
##   Surrogate splits:
##       age           < 84.5   to the left,  agree=0.651, adj=0.267, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.619, adj=0.200, (0 split)
##       osteoporosis  < 0.5    to the left,  agree=0.603, adj=0.167, (0 split)
##       kidney        < 0.5    to the left,  agree=0.556, adj=0.067, (0 split)
## 
## Node number 1671: 25 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.52  P(node) =0.00125
##     class counts:    12     6     2     5     0
##    probabilities: 0.480 0.240 0.080 0.200 0.000 
##   left son=3342 (10 obs) right son=3343 (15 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=2.8400000, (0 missing)
##       age               < 83     to the left,  improve=1.6400000, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.2893510, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.2400000, (0 missing)
##       reimbursement2008 < 2250   to the right, improve=0.3964103, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1705   to the left,  agree=0.72, adj=0.3, (0 split)
## 
## Node number 1672: 218 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.3899083  P(node) =0.0109
##     class counts:   133    56    18    10     1
##    probabilities: 0.610 0.257 0.083 0.046 0.005 
##   left son=3344 (211 obs) right son=3345 (7 obs)
##   Primary splits:
##       reimbursement2008 < 2485   to the left,  improve=2.3387790, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.3542280, (0 missing)
##       age               < 65.5   to the left,  improve=1.2410730, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3575472, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3120983, (0 missing)
## 
## Node number 1673: 10 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0005
##     class counts:     2     5     2     1     0
##    probabilities: 0.200 0.500 0.200 0.100 0.000 
## 
## Node number 1674: 26 observations,    complexity param=0.000380286
##   predicted class=B2  expected loss=0.6153846  P(node) =0.0013
##     class counts:     9    10     3     4     0
##    probabilities: 0.346 0.385 0.115 0.154 0.000 
##   left son=3348 (18 obs) right son=3349 (8 obs)
##   Primary splits:
##       age               < 54.5   to the right, improve=1.24359000, (0 missing)
##       reimbursement2008 < 1790   to the right, improve=1.21978000, (0 missing)
##       copd              < 0.5    to the left,  improve=0.92692310, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.88247860, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.04055944, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1620   to the right, agree=0.769, adj=0.25, (0 split)
## 
## Node number 1675: 7 observations
##   predicted class=B3  expected loss=0.2857143  P(node) =0.00035
##     class counts:     0     2     5     0     0
##    probabilities: 0.000 0.286 0.714 0.000 0.000 
## 
## Node number 1676: 115 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.5826087  P(node) =0.00575
##     class counts:    48    46    11     8     2
##    probabilities: 0.417 0.400 0.096 0.070 0.017 
##   left son=3352 (98 obs) right son=3353 (17 obs)
##   Primary splits:
##       age               < 55.5   to the right, improve=1.4583540, (0 missing)
##       reimbursement2008 < 2165   to the left,  improve=1.1979300, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.7250725, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7110961, (0 missing)
##       kidney            < 0.5    to the right, improve=0.5440382, (0 missing)
## 
## Node number 1677: 31 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.516129  P(node) =0.00155
##     class counts:     8    15     8     0     0
##    probabilities: 0.258 0.484 0.258 0.000 0.000 
##   left son=3354 (23 obs) right son=3355 (8 obs)
##   Primary splits:
##       age               < 62     to the right, improve=1.4824680, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.0802950, (0 missing)
##       reimbursement2008 < 2375   to the right, improve=0.9813243, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.4108830, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.3776091, (0 missing)
## 
## Node number 1678: 11 observations
##   predicted class=B1  expected loss=0.4545455  P(node) =0.00055
##     class counts:     6     4     1     0     0
##    probabilities: 0.545 0.364 0.091 0.000 0.000 
## 
## Node number 1679: 25 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.64  P(node) =0.00125
##     class counts:     9     3     9     3     1
##    probabilities: 0.360 0.120 0.360 0.120 0.040 
##   left son=3358 (8 obs) right son=3359 (17 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=1.0982350, (0 missing)
##       reimbursement2008 < 1975   to the right, improve=1.0805130, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.8988889, (0 missing)
##       age               < 62     to the right, improve=0.7600000, (0 missing)
##       kidney            < 0.5    to the right, improve=0.3850000, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1680   to the left,  agree=0.76, adj=0.250, (0 split)
##       arthritis         < 0.5    to the right, agree=0.72, adj=0.125, (0 split)
## 
## Node number 1712: 62 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.3225806  P(node) =0.0031
##     class counts:    42    11     4     4     1
##    probabilities: 0.677 0.177 0.065 0.065 0.016 
##   left son=3424 (28 obs) right son=3425 (34 obs)
##   Primary splits:
##       heart.failure < 0.5    to the right, improve=1.6485500, (0 missing)
##       arthritis     < 0.5    to the left,  improve=0.7549923, (0 missing)
##       diabetes      < 0.5    to the left,  improve=0.7121352, (0 missing)
##       age           < 65.5   to the right, improve=0.6478495, (0 missing)
##       kidney        < 0.5    to the left,  improve=0.6010580, (0 missing)
##   Surrogate splits:
##       age               < 64.5   to the left,  agree=0.629, adj=0.179, (0 split)
##       reimbursement2008 < 1640   to the left,  agree=0.629, adj=0.179, (0 split)
##       arthritis         < 0.5    to the right, agree=0.581, adj=0.071, (0 split)
##       osteoporosis      < 0.5    to the right, agree=0.581, adj=0.071, (0 split)
## 
## Node number 1713: 14 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0007
##     class counts:     6     7     0     1     0
##    probabilities: 0.429 0.500 0.000 0.071 0.000 
## 
## Node number 1714: 54 observations,    complexity param=0.0004563432
##   predicted class=B1  expected loss=0.6111111  P(node) =0.0027
##     class counts:    21    17    12     4     0
##    probabilities: 0.389 0.315 0.222 0.074 0.000 
##   left son=3428 (25 obs) right son=3429 (29 obs)
##   Primary splits:
##       reimbursement2008 < 2305   to the right, improve=1.9598980, (0 missing)
##       kidney            < 0.5    to the right, improve=0.8518519, (0 missing)
##       age               < 47.5   to the left,  improve=0.7033011, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6296296, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.4470899, (0 missing)
##   Surrogate splits:
##       age          < 67.5   to the left,  agree=0.593, adj=0.12, (0 split)
##       kidney       < 0.5    to the right, agree=0.593, adj=0.12, (0 split)
##       osteoporosis < 0.5    to the left,  agree=0.574, adj=0.08, (0 split)
##       copd         < 0.5    to the right, agree=0.556, adj=0.04, (0 split)
##       diabetes     < 0.5    to the left,  agree=0.556, adj=0.04, (0 split)
## 
## Node number 1715: 32 observations
##   predicted class=B2  expected loss=0.4375  P(node) =0.0016
##     class counts:     7    18     4     3     0
##    probabilities: 0.219 0.562 0.125 0.094 0.000 
## 
## Node number 1716: 8 observations
##   predicted class=B1  expected loss=0.375  P(node) =0.0004
##     class counts:     5     2     1     0     0
##    probabilities: 0.625 0.250 0.125 0.000 0.000 
## 
## Node number 1717: 109 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.4678899  P(node) =0.00545
##     class counts:    34    58    16     1     0
##    probabilities: 0.312 0.532 0.147 0.009 0.000 
##   left son=3434 (10 obs) right son=3435 (99 obs)
##   Primary splits:
##       reimbursement2008 < 2375   to the right, improve=1.1662310, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.6716092, (0 missing)
##       age               < 77.5   to the right, improve=0.6449413, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.4027486, (0 missing)
##       copd              < 0.5    to the right, improve=0.3923570, (0 missing)
## 
## Node number 1730: 37 observations
##   predicted class=B1  expected loss=0.4054054  P(node) =0.00185
##     class counts:    22    10     3     2     0
##    probabilities: 0.595 0.270 0.081 0.054 0.000 
## 
## Node number 1731: 10 observations
##   predicted class=B2  expected loss=0.4  P(node) =0.0005
##     class counts:     4     6     0     0     0
##    probabilities: 0.400 0.600 0.000 0.000 0.000 
## 
## Node number 1732: 23 observations
##   predicted class=B1  expected loss=0.173913  P(node) =0.00115
##     class counts:    19     2     2     0     0
##    probabilities: 0.826 0.087 0.087 0.000 0.000 
## 
## Node number 1733: 69 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4492754  P(node) =0.00345
##     class counts:    38    19     8     4     0
##    probabilities: 0.551 0.275 0.116 0.058 0.000 
##   left son=3466 (14 obs) right son=3467 (55 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the right, improve=1.5175230, (0 missing)
##       age               < 83.5   to the left,  improve=1.3893230, (0 missing)
##       copd              < 0.5    to the left,  improve=1.2426350, (0 missing)
##       reimbursement2008 < 2575   to the right, improve=0.9229627, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.3642763, (0 missing)
## 
## Node number 1734: 104 observations,    complexity param=0.0002662002
##   predicted class=B1  expected loss=0.5192308  P(node) =0.0052
##     class counts:    50    29    19     4     2
##    probabilities: 0.481 0.279 0.183 0.038 0.019 
##   left son=3468 (58 obs) right son=3469 (46 obs)
##   Primary splits:
##       age               < 79.5   to the left,  improve=2.1095890, (0 missing)
##       reimbursement2008 < 2985   to the right, improve=0.9038462, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7115385, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.6589459, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.5448718, (0 missing)
##   Surrogate splits:
##       depression < 0.5    to the left,  agree=0.577, adj=0.043, (0 split)
## 
## Node number 1735: 17 observations
##   predicted class=B2  expected loss=0.4117647  P(node) =0.00085
##     class counts:     3    10     3     1     0
##    probabilities: 0.176 0.588 0.176 0.059 0.000 
## 
## Node number 1744: 8 observations
##   predicted class=B1  expected loss=0.125  P(node) =0.0004
##     class counts:     7     1     0     0     0
##    probabilities: 0.875 0.125 0.000 0.000 0.000 
## 
## Node number 1745: 125 observations,    complexity param=0.0006084576
##   predicted class=B1  expected loss=0.552  P(node) =0.00625
##     class counts:    56    47    11    11     0
##    probabilities: 0.448 0.376 0.088 0.088 0.000 
##   left son=3490 (67 obs) right son=3491 (58 obs)
##   Primary splits:
##       reimbursement2008 < 2925   to the left,  improve=2.8552090, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=1.9365760, (0 missing)
##       age               < 69.5   to the right, improve=1.3716470, (0 missing)
##       depression        < 0.5    to the left,  improve=1.2843600, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.7595364, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.920, adj=0.828, (0 split)
##       age        < 68.5   to the right, agree=0.560, adj=0.052, (0 split)
##       cancer     < 0.5    to the left,  agree=0.544, adj=0.017, (0 split)
##       depression < 0.5    to the left,  agree=0.544, adj=0.017, (0 split)
## 
## Node number 1750: 10 observations
##   predicted class=B2  expected loss=0.3  P(node) =0.0005
##     class counts:     1     7     1     1     0
##    probabilities: 0.100 0.700 0.100 0.100 0.000 
## 
## Node number 1751: 46 observations,    complexity param=0.0003549336
##   predicted class=B2  expected loss=0.6956522  P(node) =0.0023
##     class counts:    12    14    13     7     0
##    probabilities: 0.261 0.304 0.283 0.152 0.000 
##   left son=3502 (39 obs) right son=3503 (7 obs)
##   Primary splits:
##       reimbursement2008 < 2845   to the right, improve=1.2541810, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7267081, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=0.6921773, (0 missing)
##       age               < 79.5   to the left,  improve=0.6284938, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6278986, (0 missing)
## 
## Node number 1760: 104 observations,    complexity param=0.0002788764
##   predicted class=B2  expected loss=0.5480769  P(node) =0.0052
##     class counts:    38    47    14     4     1
##    probabilities: 0.365 0.452 0.135 0.038 0.010 
##   left son=3520 (40 obs) right son=3521 (64 obs)
##   Primary splits:
##       reimbursement2008 < 2785   to the right, improve=0.8831731, (0 missing)
##       age               < 44.5   to the right, improve=0.5618273, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4772990, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.4681073, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4366792, (0 missing)
##   Surrogate splits:
##       age < 66.5   to the left,  agree=0.673, adj=0.15, (0 split)
## 
## Node number 1761: 38 observations,    complexity param=0.0002788764
##   predicted class=B2  expected loss=0.6315789  P(node) =0.0019
##     class counts:    11    14    13     0     0
##    probabilities: 0.289 0.368 0.342 0.000 0.000 
##   left son=3522 (12 obs) right son=3523 (26 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the right, improve=2.018219, (0 missing)
##       copd              < 0.5    to the left,  improve=1.710526, (0 missing)
##       reimbursement2008 < 2585   to the right, improve=1.660526, (0 missing)
##       age               < 67     to the left,  improve=1.530526, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.453383, (0 missing)
##   Surrogate splits:
##       age               < 49     to the left,  agree=0.789, adj=0.333, (0 split)
##       depression        < 0.5    to the right, agree=0.711, adj=0.083, (0 split)
##       reimbursement2008 < 2535   to the left,  agree=0.711, adj=0.083, (0 split)
## 
## Node number 1776: 11 observations
##   predicted class=B2  expected loss=0.3636364  P(node) =0.00055
##     class counts:     3     7     1     0     0
##    probabilities: 0.273 0.636 0.091 0.000 0.000 
## 
## Node number 1777: 29 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.5172414  P(node) =0.00145
##     class counts:    14     9     4     1     1
##    probabilities: 0.483 0.310 0.138 0.034 0.034 
##   left son=3554 (11 obs) right son=3555 (18 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=2.6659700, (0 missing)
##       age               < 70.5   to the left,  improve=1.7117970, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.7085386, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.6760711, (0 missing)
##       reimbursement2008 < 3195   to the right, improve=0.4333554, (0 missing)
##   Surrogate splits:
##       depression        < 0.5    to the left,  agree=0.69, adj=0.182, (0 split)
##       reimbursement2008 < 3105   to the left,  agree=0.69, adj=0.182, (0 split)
## 
## Node number 1794: 64 observations
##   predicted class=B1  expected loss=0.265625  P(node) =0.0032
##     class counts:    47    10     4     3     0
##    probabilities: 0.734 0.156 0.062 0.047 0.000 
## 
## Node number 1795: 30 observations,    complexity param=0.0001014096
##   predicted class=B1  expected loss=0.4666667  P(node) =0.0015
##     class counts:    16    10     3     1     0
##    probabilities: 0.533 0.333 0.100 0.033 0.000 
##   left son=3590 (23 obs) right son=3591 (7 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=1.1043480, (0 missing)
##       age               < 78.5   to the left,  improve=0.6035714, (0 missing)
##       reimbursement2008 < 4575   to the right, improve=0.2593301, (0 missing)
##       kidney            < 0.5    to the right, improve=0.1863636, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 7295   to the left,  agree=0.833, adj=0.286, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.833, adj=0.286, (0 split)
## 
## Node number 1796: 22 observations
##   predicted class=B1  expected loss=0.1363636  P(node) =0.0011
##     class counts:    19     2     1     0     0
##    probabilities: 0.864 0.091 0.045 0.000 0.000 
## 
## Node number 1797: 67 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.4328358  P(node) =0.00335
##     class counts:    38    19     6     3     1
##    probabilities: 0.567 0.284 0.090 0.045 0.015 
##   left son=3594 (56 obs) right son=3595 (11 obs)
##   Primary splits:
##       reimbursement2008 < 10695  to the right, improve=1.6978100, (0 missing)
##       age               < 79.5   to the left,  improve=1.5082190, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.4828650, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.8686780, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6091704, (0 missing)
##   Surrogate splits:
##       age < 51.5   to the right, agree=0.851, adj=0.091, (0 split)
## 
## Node number 1798: 105 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.4380952  P(node) =0.00525
##     class counts:    59    27    17     2     0
##    probabilities: 0.562 0.257 0.162 0.019 0.000 
##   left son=3596 (8 obs) right son=3597 (97 obs)
##   Primary splits:
##       age               < 88.5   to the right, improve=1.2302650, (0 missing)
##       reimbursement2008 < 5125   to the right, improve=1.1629710, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8149030, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.6619048, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.3031746, (0 missing)
## 
## Node number 1799: 16 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0008
##     class counts:     2     8     4     1     1
##    probabilities: 0.125 0.500 0.250 0.062 0.062 
## 
## Node number 1804: 26 observations
##   predicted class=B1  expected loss=0.3461538  P(node) =0.0013
##     class counts:    17     7     2     0     0
##    probabilities: 0.654 0.269 0.077 0.000 0.000 
## 
## Node number 1805: 34 observations,    complexity param=0.0003549336
##   predicted class=B2  expected loss=0.5294118  P(node) =0.0017
##     class counts:    13    16     3     2     0
##    probabilities: 0.382 0.471 0.088 0.059 0.000 
##   left son=3610 (22 obs) right son=3611 (12 obs)
##   Primary splits:
##       age               < 83.5   to the left,  improve=1.2843140, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5294118, (0 missing)
##       reimbursement2008 < 8165   to the right, improve=0.4298164, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.4298164, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.3587538, (0 missing)
##   Surrogate splits:
##       kidney            < 0.5    to the left,  agree=0.735, adj=0.250, (0 split)
##       reimbursement2008 < 9210   to the left,  agree=0.735, adj=0.250, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.676, adj=0.083, (0 split)
## 
## Node number 1822: 22 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5  P(node) =0.0011
##     class counts:     7    11     3     1     0
##    probabilities: 0.318 0.500 0.136 0.045 0.000 
##   left son=3644 (7 obs) right son=3645 (15 obs)
##   Primary splits:
##       reimbursement2008 < 14605  to the left,  improve=1.8372290, (0 missing)
##       copd              < 0.5    to the right, improve=0.6045066, (0 missing)
##       age               < 83.5   to the left,  improve=0.5454545, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4658009, (0 missing)
##       bucket2008        < 3.5    to the right, improve=0.4181818, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the left,  agree=0.773, adj=0.286, (0 split)
##       age        < 77     to the left,  agree=0.727, adj=0.143, (0 split)
## 
## Node number 1823: 32 observations,    complexity param=0.0003549336
##   predicted class=B3  expected loss=0.59375  P(node) =0.0016
##     class counts:    11     7    13     1     0
##    probabilities: 0.344 0.219 0.406 0.031 0.000 
##   left son=3646 (9 obs) right son=3647 (23 obs)
##   Primary splits:
##       copd              < 0.5    to the right, improve=1.4619570, (0 missing)
##       reimbursement2008 < 7995   to the left,  improve=1.1931820, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.1931820, (0 missing)
##       age               < 77.5   to the right, improve=0.7692857, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.6765873, (0 missing)
##   Surrogate splits:
##       kidney < 0.5    to the right, agree=0.812, adj=0.333, (0 split)
##       stroke < 0.5    to the right, agree=0.812, adj=0.333, (0 split)
## 
## Node number 1828: 18 observations
##   predicted class=B1  expected loss=0.3888889  P(node) =0.0009
##     class counts:    11     3     0     4     0
##    probabilities: 0.611 0.167 0.000 0.222 0.000 
## 
## Node number 1829: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     2     4     0     1     0
##    probabilities: 0.286 0.571 0.000 0.143 0.000 
## 
## Node number 1872: 11 observations
##   predicted class=B2  expected loss=0.4545455  P(node) =0.00055
##     class counts:     5     6     0     0     0
##    probabilities: 0.455 0.545 0.000 0.000 0.000 
## 
## Node number 1873: 16 observations
##   predicted class=B1  expected loss=0.3125  P(node) =0.0008
##     class counts:    11     2     2     1     0
##    probabilities: 0.688 0.125 0.125 0.062 0.000 
## 
## Node number 1874: 7 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.00035
##     class counts:     4     2     1     0     0
##    probabilities: 0.571 0.286 0.143 0.000 0.000 
## 
## Node number 1875: 38 observations,    complexity param=7.60572e-05
##   predicted class=B2  expected loss=0.3684211  P(node) =0.0019
##     class counts:     8    24     4     2     0
##    probabilities: 0.211 0.632 0.105 0.053 0.000 
##   left son=3750 (13 obs) right son=3751 (25 obs)
##   Primary splits:
##       reimbursement2008 < 4175   to the left,  improve=1.2469640, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3250655, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.3030075, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2482456, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.2387218, (0 missing)
##   Surrogate splits:
##       age          < 58.5   to the left,  agree=0.711, adj=0.154, (0 split)
##       osteoporosis < 0.5    to the right, agree=0.711, adj=0.154, (0 split)
## 
## Node number 1878: 13 observations
##   predicted class=B2  expected loss=0.3076923  P(node) =0.00065
##     class counts:     2     9     1     1     0
##    probabilities: 0.154 0.692 0.077 0.077 0.000 
## 
## Node number 1879: 39 observations,    complexity param=0.0003549336
##   predicted class=B3  expected loss=0.6410256  P(node) =0.00195
##     class counts:     9    13    14     3     0
##    probabilities: 0.231 0.333 0.359 0.077 0.000 
##   left son=3758 (25 obs) right son=3759 (14 obs)
##   Primary splits:
##       reimbursement2008 < 5860   to the right, improve=2.5504760, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.1111110, (0 missing)
##       age               < 69.5   to the right, improve=1.0712640, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.7000000, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.6969697, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.795, adj=0.429, (0 split)
##       age        < 68.5   to the right, agree=0.769, adj=0.357, (0 split)
## 
## Node number 1882: 26 observations
##   predicted class=B1  expected loss=0.5769231  P(node) =0.0013
##     class counts:    11     5     5     5     0
##    probabilities: 0.423 0.192 0.192 0.192 0.000 
## 
## Node number 1883: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     1     2     4     0     0
##    probabilities: 0.143 0.286 0.571 0.000 0.000 
## 
## Node number 1912: 30 observations,    complexity param=0.000253524
##   predicted class=B1  expected loss=0.6333333  P(node) =0.0015
##     class counts:    11    11     5     3     0
##    probabilities: 0.367 0.367 0.167 0.100 0.000 
##   left son=3824 (15 obs) right son=3825 (15 obs)
##   Primary splits:
##       age               < 68.5   to the right, improve=1.4666670, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.0009570, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9900452, (0 missing)
##       reimbursement2008 < 7610   to the right, improve=0.7130435, (0 missing)
##       kidney            < 0.5    to the right, improve=0.5222222, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 6645   to the left,  agree=0.667, adj=0.333, (0 split)
##       alzheimers        < 0.5    to the right, agree=0.600, adj=0.200, (0 split)
##       arthritis         < 0.5    to the left,  agree=0.533, adj=0.067, (0 split)
##       cancer            < 0.5    to the right, agree=0.533, adj=0.067, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.533, adj=0.067, (0 split)
## 
## Node number 1913: 11 observations
##   predicted class=B2  expected loss=0.5454545  P(node) =0.00055
##     class counts:     0     5     5     1     0
##    probabilities: 0.000 0.455 0.455 0.091 0.000 
## 
## Node number 1914: 31 observations
##   predicted class=B2  expected loss=0.4193548  P(node) =0.00155
##     class counts:     3    18     8     2     0
##    probabilities: 0.097 0.581 0.258 0.065 0.000 
## 
## Node number 1915: 7 observations
##   predicted class=B3  expected loss=0.2857143  P(node) =0.00035
##     class counts:     1     1     5     0     0
##    probabilities: 0.143 0.143 0.714 0.000 0.000 
## 
## Node number 1920: 32 observations,    complexity param=0.0003422574
##   predicted class=B1  expected loss=0.53125  P(node) =0.0016
##     class counts:    15    15     2     0     0
##    probabilities: 0.469 0.469 0.062 0.000 0.000 
##   left son=3840 (8 obs) right son=3841 (24 obs)
##   Primary splits:
##       age               < 57.5   to the left,  improve=0.8125000, (0 missing)
##       reimbursement2008 < 7940   to the right, improve=0.7690217, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.7690217, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.7034091, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3958333, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 8620   to the right, agree=0.812, adj=0.25, (0 split)
## 
## Node number 1921: 123 observations,    complexity param=0.0003422574
##   predicted class=B1  expected loss=0.495935  P(node) =0.00615
##     class counts:    62    32    26     3     0
##    probabilities: 0.504 0.260 0.211 0.024 0.000 
##   left son=3842 (19 obs) right son=3843 (104 obs)
##   Primary splits:
##       reimbursement2008 < 5150   to the right, improve=2.8759260, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.1396420, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6208037, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4917080, (0 missing)
##       age               < 59.5   to the left,  improve=0.4634146, (0 missing)
##   Surrogate splits:
##       age < 32.5   to the left,  agree=0.862, adj=0.105, (0 split)
## 
## Node number 1924: 31 observations,    complexity param=0.000507048
##   predicted class=B1  expected loss=0.6129032  P(node) =0.00155
##     class counts:    12    11     2     5     1
##    probabilities: 0.387 0.355 0.065 0.161 0.032 
##   left son=3848 (7 obs) right son=3849 (24 obs)
##   Primary splits:
##       age               < 67.5   to the right, improve=2.6862520, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9410138, (0 missing)
##       reimbursement2008 < 24480  to the left,  improve=0.8052995, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.6933948, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.4838710, (0 missing)
## 
## Node number 1925: 21 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.6666667  P(node) =0.00105
##     class counts:     4     5     7     5     0
##    probabilities: 0.190 0.238 0.333 0.238 0.000 
##   left son=3850 (13 obs) right son=3851 (8 obs)
##   Primary splits:
##       age               < 56.5   to the right, improve=0.8507326, (0 missing)
##       reimbursement2008 < 16675  to the left,  improve=0.6692641, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5815018, (0 missing)
##       bucket2008        < 3.5    to the right, improve=0.4853480, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4682540, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 16065  to the right, agree=0.667, adj=0.125, (0 split)
## 
## Node number 1926: 15 observations
##   predicted class=B1  expected loss=0.6  P(node) =0.00075
##     class counts:     6     3     5     1     0
##    probabilities: 0.400 0.200 0.333 0.067 0.000 
## 
## Node number 1927: 11 observations
##   predicted class=B3  expected loss=0.4545455  P(node) =0.00055
##     class counts:     2     0     6     3     0
##    probabilities: 0.182 0.000 0.545 0.273 0.000 
## 
## Node number 1928: 144 observations,    complexity param=0.0004563432
##   predicted class=B1  expected loss=0.5069444  P(node) =0.0072
##     class counts:    71    49    15     9     0
##    probabilities: 0.493 0.340 0.104 0.063 0.000 
##   left son=3856 (117 obs) right son=3857 (27 obs)
##   Primary splits:
##       age               < 73.5   to the right, improve=1.6075500, (0 missing)
##       reimbursement2008 < 5230   to the left,  improve=1.4092590, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6035354, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.5234020, (0 missing)
##       copd              < 0.5    to the right, improve=0.3870370, (0 missing)
## 
## Node number 1929: 26 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6538462  P(node) =0.0013
##     class counts:     7     9     8     1     1
##    probabilities: 0.269 0.346 0.308 0.038 0.038 
##   left son=3858 (7 obs) right son=3859 (19 obs)
##   Primary splits:
##       age               < 92.5   to the right, improve=1.7397340, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.4865380, (0 missing)
##       reimbursement2008 < 13275  to the left,  improve=1.1004270, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7115385, (0 missing)
##       copd              < 0.5    to the right, improve=0.6153846, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 5905   to the left,  agree=0.769, adj=0.143, (0 split)
## 
## Node number 1930: 28 observations,    complexity param=0.0006084576
##   predicted class=B1  expected loss=0.4642857  P(node) =0.0014
##     class counts:    15     9     1     2     1
##    probabilities: 0.536 0.321 0.036 0.071 0.036 
##   left son=3860 (17 obs) right son=3861 (11 obs)
##   Primary splits:
##       age               < 94.5   to the left,  improve=3.2207790, (0 missing)
##       reimbursement2008 < 15610  to the left,  improve=1.3333330, (0 missing)
##       copd              < 0.5    to the left,  improve=1.1488100, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.0091900, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7619048, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 18790  to the left,  agree=0.679, adj=0.182, (0 split)
##       bucket2008        < 3.5    to the left,  agree=0.679, adj=0.182, (0 split)
## 
## Node number 1931: 129 observations,    complexity param=0.0004056384
##   predicted class=B2  expected loss=0.5503876  P(node) =0.00645
##     class counts:    34    58    26    10     1
##    probabilities: 0.264 0.450 0.202 0.078 0.008 
##   left son=3862 (61 obs) right son=3863 (68 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=2.320337, (0 missing)
##       copd              < 0.5    to the left,  improve=1.845030, (0 missing)
##       reimbursement2008 < 6885   to the right, improve=1.627912, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.372989, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.116088, (0 missing)
##   Surrogate splits:
##       age               < 82.5   to the right, agree=0.597, adj=0.148, (0 split)
##       reimbursement2008 < 14610  to the left,  agree=0.566, adj=0.082, (0 split)
##       bucket2008        < 3.5    to the left,  agree=0.566, adj=0.082, (0 split)
##       ihd               < 0.5    to the left,  agree=0.535, adj=0.016, (0 split)
## 
## Node number 1932: 64 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.40625  P(node) =0.0032
##     class counts:    17    38     7     2     0
##    probabilities: 0.266 0.594 0.109 0.031 0.000 
##   left son=3864 (50 obs) right son=3865 (14 obs)
##   Primary splits:
##       reimbursement2008 < 4345   to the left,  improve=4.173750, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.653328, (0 missing)
##       age               < 72.5   to the left,  improve=1.548721, (0 missing)
##       depression        < 0.5    to the left,  improve=0.793750, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.494532, (0 missing)
## 
## Node number 1933: 10 observations
##   predicted class=B2  expected loss=0  P(node) =0.0005
##     class counts:     0    10     0     0     0
##    probabilities: 0.000 1.000 0.000 0.000 0.000 
## 
## Node number 1934: 9 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.00045
##     class counts:     6     1     2     0     0
##    probabilities: 0.667 0.111 0.222 0.000 0.000 
## 
## Node number 1935: 104 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.4903846  P(node) =0.0052
##     class counts:    28    53    18     5     0
##    probabilities: 0.269 0.510 0.173 0.048 0.000 
##   left son=3870 (37 obs) right son=3871 (67 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=1.7427860, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.3422740, (0 missing)
##       stroke            < 0.5    to the right, improve=1.1791950, (0 missing)
##       reimbursement2008 < 4030   to the left,  improve=1.0517090, (0 missing)
##       age               < 80.5   to the left,  improve=0.6396844, (0 missing)
##   Surrogate splits:
##       stroke < 0.5    to the right, agree=0.654, adj=0.027, (0 split)
## 
## Node number 1946: 49 observations,    complexity param=0.0005324004
##   predicted class=B1  expected loss=0.6734694  P(node) =0.00245
##     class counts:    16    13    16     4     0
##    probabilities: 0.327 0.265 0.327 0.082 0.000 
##   left son=3892 (16 obs) right son=3893 (33 obs)
##   Primary splits:
##       copd              < 0.5    to the right, improve=1.7300560, (0 missing)
##       reimbursement2008 < 5825   to the left,  improve=1.6040820, (0 missing)
##       age               < 67.5   to the right, improve=1.2805610, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.0381360, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8306573, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 25990  to the right, agree=0.755, adj=0.250, (0 split)
##       age               < 65.5   to the left,  agree=0.735, adj=0.188, (0 split)
##       bucket2008        < 3.5    to the right, agree=0.735, adj=0.188, (0 split)
## 
## Node number 1947: 63 observations,    complexity param=0.0005324004
##   predicted class=B2  expected loss=0.5873016  P(node) =0.00315
##     class counts:     8    26    22     7     0
##    probabilities: 0.127 0.413 0.349 0.111 0.000 
##   left son=3894 (33 obs) right son=3895 (30 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=2.2784990, (0 missing)
##       age               < 73.5   to the left,  improve=1.4389340, (0 missing)
##       reimbursement2008 < 14505  to the left,  improve=1.1107860, (0 missing)
##       copd              < 0.5    to the left,  improve=0.7714286, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6362229, (0 missing)
##   Surrogate splits:
##       alzheimers        < 0.5    to the left,  agree=0.651, adj=0.267, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.635, adj=0.233, (0 split)
##       reimbursement2008 < 13275  to the left,  agree=0.635, adj=0.233, (0 split)
##       copd              < 0.5    to the left,  agree=0.587, adj=0.133, (0 split)
##       stroke            < 0.5    to the left,  agree=0.587, adj=0.133, (0 split)
## 
## Node number 1968: 38 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5  P(node) =0.0019
##     class counts:    19    12     2     4     1
##    probabilities: 0.500 0.316 0.053 0.105 0.026 
##   left son=3936 (30 obs) right son=3937 (8 obs)
##   Primary splits:
##       age               < 67.5   to the right, improve=1.4745610, (0 missing)
##       reimbursement2008 < 14135  to the left,  improve=0.7888471, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5412281, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.5108359, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=0.3373819, (0 missing)
## 
## Node number 1969: 18 observations
##   predicted class=B2  expected loss=0.5555556  P(node) =0.0009
##     class counts:     2     8     4     2     2
##    probabilities: 0.111 0.444 0.222 0.111 0.111 
## 
## Node number 1970: 85 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5529412  P(node) =0.00425
##     class counts:    27    38    11     8     1
##    probabilities: 0.318 0.447 0.129 0.094 0.012 
##   left son=3940 (59 obs) right son=3941 (26 obs)
##   Primary splits:
##       age               < 80.5   to the left,  improve=1.2457550, (0 missing)
##       reimbursement2008 < 5820   to the left,  improve=1.0846660, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7174773, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5925134, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3022536, (0 missing)
## 
## Node number 1971: 42 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.452381  P(node) =0.0021
##     class counts:     4    23     6     9     0
##    probabilities: 0.095 0.548 0.143 0.214 0.000 
##   left son=3942 (32 obs) right son=3943 (10 obs)
##   Primary splits:
##       age               < 67.5   to the right, improve=2.2755950, (0 missing)
##       reimbursement2008 < 6595   to the right, improve=0.5809524, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.2880952, (0 missing)
##       copd              < 0.5    to the right, improve=0.2861722, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.1707875, (0 missing)
## 
## Node number 1972: 16 observations
##   predicted class=B1  expected loss=0.625  P(node) =0.0008
##     class counts:     6     6     4     0     0
##    probabilities: 0.375 0.375 0.250 0.000 0.000 
## 
## Node number 1973: 21 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5714286  P(node) =0.00105
##     class counts:     4     9     1     7     0
##    probabilities: 0.190 0.429 0.048 0.333 0.000 
##   left son=3946 (10 obs) right son=3947 (11 obs)
##   Primary splits:
##       age               < 87     to the right, improve=0.9454545, (0 missing)
##       copd              < 0.5    to the right, improve=0.9423077, (0 missing)
##       reimbursement2008 < 10955  to the right, improve=0.4545455, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.2307692, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.1923077, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4780   to the right, agree=0.667, adj=0.3, (0 split)
##       osteoporosis      < 0.5    to the right, agree=0.619, adj=0.2, (0 split)
##       cancer            < 0.5    to the right, agree=0.571, adj=0.1, (0 split)
##       copd              < 0.5    to the right, agree=0.571, adj=0.1, (0 split)
## 
## Node number 1974: 17 observations
##   predicted class=B2  expected loss=0.2352941  P(node) =0.00085
##     class counts:     1    13     2     1     0
##    probabilities: 0.059 0.765 0.118 0.059 0.000 
## 
## Node number 1975: 45 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4666667  P(node) =0.00225
##     class counts:     5    24    14     2     0
##    probabilities: 0.111 0.533 0.311 0.044 0.000 
##   left son=3950 (23 obs) right son=3951 (22 obs)
##   Primary splits:
##       reimbursement2008 < 5595   to the left,  improve=2.8877470, (0 missing)
##       age               < 70.5   to the left,  improve=0.7770751, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4450593, (0 missing)
##       copd              < 0.5    to the right, improve=0.2106952, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1447005, (0 missing)
##   Surrogate splits:
##       osteoporosis  < 0.5    to the right, agree=0.667, adj=0.318, (0 split)
##       age           < 70.5   to the left,  agree=0.622, adj=0.227, (0 split)
##       bucket2008    < 2.5    to the left,  agree=0.622, adj=0.227, (0 split)
##       copd          < 0.5    to the left,  agree=0.578, adj=0.136, (0 split)
##       heart.failure < 0.5    to the right, agree=0.578, adj=0.136, (0 split)
## 
## Node number 1978: 216 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5462963  P(node) =0.0108
##     class counts:    42    98    56    18     2
##    probabilities: 0.194 0.454 0.259 0.083 0.009 
##   left son=3956 (52 obs) right son=3957 (164 obs)
##   Primary splits:
##       reimbursement2008 < 15105  to the right, improve=1.4684180, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.4512310, (0 missing)
##       age               < 71.5   to the right, improve=1.0436270, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8503280, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7569892, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.926, adj=0.692, (0 split)
##       age        < 55.5   to the left,  agree=0.764, adj=0.019, (0 split)
## 
## Node number 1979: 9 observations
##   predicted class=B3  expected loss=0.5555556  P(node) =0.00045
##     class counts:     1     1     4     3     0
##    probabilities: 0.111 0.111 0.444 0.333 0.000 
## 
## Node number 1984: 43 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5813953  P(node) =0.00215
##     class counts:    18     9    12     2     2
##    probabilities: 0.419 0.209 0.279 0.047 0.047 
##   left son=3968 (11 obs) right son=3969 (32 obs)
##   Primary splits:
##       reimbursement2008 < 8495   to the left,  improve=2.1203750, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.3253000, (0 missing)
##       age               < 96.5   to the left,  improve=1.2164460, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9252995, (0 missing)
##       copd              < 0.5    to the right, improve=0.5070379, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.884, adj=0.545, (0 split)
## 
## Node number 1985: 24 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.625  P(node) =0.0012
##     class counts:     4     9     9     2     0
##    probabilities: 0.167 0.375 0.375 0.083 0.000 
##   left son=3970 (8 obs) right son=3971 (16 obs)
##   Primary splits:
##       reimbursement2008 < 9045   to the left,  improve=2.2916670, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8921911, (0 missing)
##       age               < 87.5   to the left,  improve=0.7722222, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.7722222, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.4166667, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.750, adj=0.250, (0 split)
##       age        < 89.5   to the right, agree=0.708, adj=0.125, (0 split)
## 
## Node number 1986: 11 observations
##   predicted class=B1  expected loss=0.4545455  P(node) =0.00055
##     class counts:     6     1     1     3     0
##    probabilities: 0.545 0.091 0.091 0.273 0.000 
## 
## Node number 1987: 268 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6231343  P(node) =0.0134
##     class counts:    60   101    49    50     8
##    probabilities: 0.224 0.377 0.183 0.187 0.030 
##   left son=3974 (177 obs) right son=3975 (91 obs)
##   Primary splits:
##       age               < 77.5   to the left,  improve=1.6839510, (0 missing)
##       reimbursement2008 < 14425  to the left,  improve=1.3251930, (0 missing)
##       stroke            < 0.5    to the right, improve=1.2532710, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.9809812, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9444366, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 13575  to the left,  agree=0.679, adj=0.055, (0 split)
## 
## Node number 1990: 235 observations,    complexity param=0.0003650745
##   predicted class=B2  expected loss=0.6042553  P(node) =0.01175
##     class counts:    45    93    59    32     6
##    probabilities: 0.191 0.396 0.251 0.136 0.026 
##   left son=3980 (210 obs) right son=3981 (25 obs)
##   Primary splits:
##       reimbursement2008 < 6170   to the left,  improve=2.3734140, (0 missing)
##       age               < 81.5   to the right, improve=1.4517590, (0 missing)
##       depression        < 0.5    to the right, improve=0.7995092, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.6947270, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6162007, (0 missing)
## 
## Node number 1991: 12 observations
##   predicted class=B3  expected loss=0.3333333  P(node) =0.0006
##     class counts:     2     2     8     0     0
##    probabilities: 0.167 0.167 0.667 0.000 0.000 
## 
## Node number 2004: 88 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.4318182  P(node) =0.0044
##     class counts:    16    50    14     7     1
##    probabilities: 0.182 0.568 0.159 0.080 0.011 
##   left son=4008 (19 obs) right son=4009 (69 obs)
##   Primary splits:
##       reimbursement2008 < 3725   to the left,  improve=1.1251130, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.9988702, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.7978634, (0 missing)
##       age               < 90.5   to the left,  improve=0.6812354, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.5300418, (0 missing)
## 
## Node number 2005: 19 observations
##   predicted class=B2  expected loss=0.2105263  P(node) =0.00095
##     class counts:     0    15     1     3     0
##    probabilities: 0.000 0.789 0.053 0.158 0.000 
## 
## Node number 2006: 16 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0008
##     class counts:     3     8     3     2     0
##    probabilities: 0.188 0.500 0.188 0.125 0.000 
## 
## Node number 2007: 9 observations
##   predicted class=B3  expected loss=0.5555556  P(node) =0.00045
##     class counts:     1     2     4     2     0
##    probabilities: 0.111 0.222 0.444 0.222 0.000 
## 
## Node number 2012: 35 observations,    complexity param=0.0002028192
##   predicted class=B3  expected loss=0.6571429  P(node) =0.00175
##     class counts:     7    11    12     5     0
##    probabilities: 0.200 0.314 0.343 0.143 0.000 
##   left son=4024 (13 obs) right son=4025 (22 obs)
##   Primary splits:
##       age               < 72.5   to the left,  improve=1.2093910, (0 missing)
##       reimbursement2008 < 6400   to the right, improve=0.9571429, (0 missing)
##       depression        < 0.5    to the right, improve=0.4095238, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.3340226, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1910973, (0 missing)
##   Surrogate splits:
##       stroke < 0.5    to the right, agree=0.657, adj=0.077, (0 split)
## 
## Node number 2013: 218 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5229358  P(node) =0.0109
##     class counts:    22   104    57    30     5
##    probabilities: 0.101 0.477 0.261 0.138 0.023 
##   left son=4026 (187 obs) right son=4027 (31 obs)
##   Primary splits:
##       reimbursement2008 < 7265   to the right, improve=1.4088950, (0 missing)
##       copd              < 0.5    to the left,  improve=1.3174740, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.2029980, (0 missing)
##       age               < 75.5   to the left,  improve=0.7552085, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.5102534, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.913, adj=0.387, (0 split)
## 
## Node number 2014: 22 observations
##   predicted class=B2  expected loss=0.2272727  P(node) =0.0011
##     class counts:     0    17     4     0     1
##    probabilities: 0.000 0.773 0.182 0.000 0.045 
## 
## Node number 2015: 10 observations
##   predicted class=B3  expected loss=0.6  P(node) =0.0005
##     class counts:     0     3     4     3     0
##    probabilities: 0.000 0.300 0.400 0.300 0.000 
## 
## Node number 2032: 67 observations,    complexity param=0.0004563432
##   predicted class=B1  expected loss=0.6716418  P(node) =0.00335
##     class counts:    22    12    17    16     0
##    probabilities: 0.328 0.179 0.254 0.239 0.000 
##   left son=4064 (59 obs) right son=4065 (8 obs)
##   Primary splits:
##       reimbursement2008 < 18390  to the right, improve=1.7171140, (0 missing)
##       stroke            < 0.5    to the right, improve=1.6606280, (0 missing)
##       cancer            < 0.5    to the right, improve=1.0990060, (0 missing)
##       age               < 80.5   to the left,  improve=0.9955676, (0 missing)
##       bucket2008        < 3.5    to the right, improve=0.8525373, (0 missing)
## 
## Node number 2033: 28 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.6071429  P(node) =0.0014
##     class counts:     5    11     3     9     0
##    probabilities: 0.179 0.393 0.107 0.321 0.000 
##   left son=4066 (9 obs) right son=4067 (19 obs)
##   Primary splits:
##       reimbursement2008 < 16540  to the left,  improve=2.1796160, (0 missing)
##       depression        < 0.5    to the left,  improve=1.2857140, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.9047619, (0 missing)
##       age               < 70.5   to the left,  improve=0.8158730, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3630952, (0 missing)
## 
## Node number 2034: 41 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5121951  P(node) =0.00205
##     class counts:     7    20     6     4     4
##    probabilities: 0.171 0.488 0.146 0.098 0.098 
##   left son=4068 (32 obs) right son=4069 (9 obs)
##   Primary splits:
##       age               < 83.5   to the left,  improve=2.1888550, (0 missing)
##       reimbursement2008 < 25405  to the right, improve=1.4735770, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9644375, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.8832995, (0 missing)
##       stroke            < 0.5    to the right, improve=0.7966955, (0 missing)
## 
## Node number 2035: 97 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6907216  P(node) =0.00485
##     class counts:    14    30    23    26     4
##    probabilities: 0.144 0.309 0.237 0.268 0.041 
##   left son=4070 (81 obs) right son=4071 (16 obs)
##   Primary splits:
##       reimbursement2008 < 21150  to the left,  improve=2.1982790, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.8385610, (0 missing)
##       age               < 58     to the right, improve=1.5250180, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.8794627, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7745519, (0 missing)
## 
## Node number 2036: 125 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.568  P(node) =0.00625
##     class counts:    17    54    32    16     6
##    probabilities: 0.136 0.432 0.256 0.128 0.048 
##   left son=4072 (36 obs) right son=4073 (89 obs)
##   Primary splits:
##       reimbursement2008 < 22510  to the right, improve=1.5030360, (0 missing)
##       age               < 71.5   to the left,  improve=1.4083000, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.0672150, (0 missing)
##       bucket2008        < 3.5    to the right, improve=1.0234450, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9386667, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.72, adj=0.028, (0 split)
## 
## Node number 2037: 15 observations
##   predicted class=B3  expected loss=0.6  P(node) =0.00075
##     class counts:     0     3     6     4     2
##    probabilities: 0.000 0.200 0.400 0.267 0.133 
## 
## Node number 2038: 13 observations
##   predicted class=B2  expected loss=0.6153846  P(node) =0.00065
##     class counts:     1     5     3     3     1
##    probabilities: 0.077 0.385 0.231 0.231 0.077 
## 
## Node number 2039: 10 observations
##   predicted class=B3  expected loss=0.1  P(node) =0.0005
##     class counts:     0     0     9     1     0
##    probabilities: 0.000 0.000 0.900 0.100 0.000 
## 
## Node number 2044: 47 observations,    complexity param=0.0002662002
##   predicted class=B2  expected loss=0.4680851  P(node) =0.00235
##     class counts:     3    25    10     6     3
##    probabilities: 0.064 0.532 0.213 0.128 0.064 
##   left son=4088 (30 obs) right son=4089 (17 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=3.2804340, (0 missing)
##       age               < 81.5   to the left,  improve=1.9668850, (0 missing)
##       reimbursement2008 < 31080  to the right, improve=1.4612460, (0 missing)
##       copd              < 0.5    to the right, improve=1.1322990, (0 missing)
##       depression        < 0.5    to the right, improve=0.8569045, (0 missing)
##   Surrogate splits:
##       age               < 85.5   to the left,  agree=0.702, adj=0.176, (0 split)
##       reimbursement2008 < 31580  to the left,  agree=0.660, adj=0.059, (0 split)
## 
## Node number 2045: 44 observations,    complexity param=0.0002662002
##   predicted class=B2  expected loss=0.5681818  P(node) =0.0022
##     class counts:     3    19     7    15     0
##    probabilities: 0.068 0.432 0.159 0.341 0.000 
##   left son=4090 (11 obs) right son=4091 (33 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=1.5454550, (0 missing)
##       age               < 55.5   to the left,  improve=1.5257990, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.3346510, (0 missing)
##       reimbursement2008 < 29895  to the right, improve=0.8874459, (0 missing)
##       stroke            < 0.5    to the right, improve=0.7160173, (0 missing)
##   Surrogate splits:
##       age < 55.5   to the left,  agree=0.773, adj=0.091, (0 split)
## 
## Node number 2046: 97 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5979381  P(node) =0.00485
##     class counts:     6    39    17    28     7
##    probabilities: 0.062 0.402 0.175 0.289 0.072 
##   left son=4092 (26 obs) right son=4093 (71 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=1.5049540, (0 missing)
##       reimbursement2008 < 37785  to the left,  improve=1.3125260, (0 missing)
##       age               < 79.5   to the left,  improve=1.1547350, (0 missing)
##       cancer            < 0.5    to the right, improve=1.1520240, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9743395, (0 missing)
##   Surrogate splits:
##       heart.failure < 0.5    to the left,  agree=0.753, adj=0.077, (0 split)
## 
## Node number 2047: 234 observations,    complexity param=0.000507048
##   predicted class=B4  expected loss=0.6709402  P(node) =0.0117
##     class counts:    18    65    63    77    11
##    probabilities: 0.077 0.278 0.269 0.329 0.047 
##   left son=4094 (180 obs) right son=4095 (54 obs)
##   Primary splits:
##       reimbursement2008 < 37290  to the right, improve=2.5176640, (0 missing)
##       bucket2008        < 4.5    to the right, improve=2.4693040, (0 missing)
##       age               < 36.5   to the left,  improve=0.9682593, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8197802, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.8182531, (0 missing)
## 
## Node number 2570: 277 observations
##   predicted class=B1  expected loss=0.1371841  P(node) =0.01385
##     class counts:   239    21    10     7     0
##    probabilities: 0.863 0.076 0.036 0.025 0.000 
## 
## Node number 2571: 430 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1837209  P(node) =0.0215
##     class counts:   351    47    26     4     2
##    probabilities: 0.816 0.109 0.060 0.009 0.005 
##   left son=5142 (398 obs) right son=5143 (32 obs)
##   Primary splits:
##       reimbursement2008 < 475    to the left,  improve=1.1570540, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.5902656, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4826179, (0 missing)
##       age               < 86.5   to the left,  improve=0.4570367, (0 missing)
##       kidney            < 0.5    to the right, improve=0.2437930, (0 missing)
## 
## Node number 2842: 60 observations
##   predicted class=B1  expected loss=0.2666667  P(node) =0.003
##     class counts:    44    12     3     1     0
##    probabilities: 0.733 0.200 0.050 0.017 0.000 
## 
## Node number 2843: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     3     4     0     0     0
##    probabilities: 0.429 0.571 0.000 0.000 0.000 
## 
## Node number 2882: 197 observations
##   predicted class=B1  expected loss=0.1928934  P(node) =0.00985
##     class counts:   159    18    13     7     0
##    probabilities: 0.807 0.091 0.066 0.036 0.000 
## 
## Node number 2883: 59 observations,    complexity param=5.07048e-05
##   predicted class=B1  expected loss=0.3389831  P(node) =0.00295
##     class counts:    39    10     8     2     0
##    probabilities: 0.661 0.169 0.136 0.034 0.000 
##   left son=5766 (51 obs) right son=5767 (8 obs)
##   Primary splits:
##       reimbursement2008 < 1115   to the right, improve=1.7797440, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.2458970, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9810446, (0 missing)
##       age               < 83.5   to the left,  improve=0.7705825, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.4388154, (0 missing)
## 
## Node number 2884: 109 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.2844037  P(node) =0.00545
##     class counts:    78    21     9     1     0
##    probabilities: 0.716 0.193 0.083 0.009 0.000 
##   left son=5768 (79 obs) right son=5769 (30 obs)
##   Primary splits:
##       age               < 77.5   to the right, improve=1.7532540, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.7212762, (0 missing)
##       reimbursement2008 < 1545   to the left,  improve=0.6234163, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.4323641, (0 missing)
##       kidney            < 0.5    to the right, improve=0.4275433, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1345   to the right, agree=0.752, adj=0.1, (0 split)
## 
## Node number 2885: 49 observations
##   predicted class=B1  expected loss=0.244898  P(node) =0.00245
##     class counts:    37     4     4     4     0
##    probabilities: 0.755 0.082 0.082 0.082 0.000 
## 
## Node number 2892: 32 observations
##   predicted class=B1  expected loss=0.1875  P(node) =0.0016
##     class counts:    26     4     1     1     0
##    probabilities: 0.813 0.125 0.031 0.031 0.000 
## 
## Node number 2893: 20 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.45  P(node) =0.001
##     class counts:    11     6     1     2     0
##    probabilities: 0.550 0.300 0.050 0.100 0.000 
##   left son=5786 (9 obs) right son=5787 (11 obs)
##   Primary splits:
##       reimbursement2008 < 1115   to the left,  improve=1.4757580, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.1500000, (0 missing)
##       age               < 54     to the right, improve=0.5666667, (0 missing)
##   Surrogate splits:
##       diabetes      < 0.5    to the left,  agree=0.75, adj=0.444, (0 split)
##       age           < 41     to the left,  agree=0.70, adj=0.333, (0 split)
##       depression    < 0.5    to the right, agree=0.60, adj=0.111, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.60, adj=0.111, (0 split)
## 
## Node number 2894: 15 observations
##   predicted class=B1  expected loss=0.2666667  P(node) =0.00075
##     class counts:    11     3     1     0     0
##    probabilities: 0.733 0.200 0.067 0.000 0.000 
## 
## Node number 2895: 20 observations,    complexity param=8.450799e-05
##   predicted class=B2  expected loss=0.45  P(node) =0.001
##     class counts:     9    11     0     0     0
##    probabilities: 0.450 0.550 0.000 0.000 0.000 
##   left son=5790 (11 obs) right son=5791 (9 obs)
##   Primary splits:
##       reimbursement2008 < 1275   to the right, improve=0.445454500, (0 missing)
##       age               < 64.5   to the left,  improve=0.100000000, (0 missing)
##       depression        < 0.5    to the left,  improve=0.001010101, (0 missing)
##   Surrogate splits:
##       age        < 46     to the right, agree=0.6, adj=0.111, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.6, adj=0.111, (0 split)
##       depression < 0.5    to the right, agree=0.6, adj=0.111, (0 split)
## 
## Node number 2948: 8 observations
##   predicted class=B1  expected loss=0  P(node) =0.0004
##     class counts:     8     0     0     0     0
##    probabilities: 1.000 0.000 0.000 0.000 0.000 
## 
## Node number 2949: 137 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.2992701  P(node) =0.00685
##     class counts:    96    25    13     3     0
##    probabilities: 0.701 0.182 0.095 0.022 0.000 
##   left son=5898 (10 obs) right son=5899 (127 obs)
##   Primary splits:
##       copd              < 0.5    to the right, improve=0.7930226, (0 missing)
##       reimbursement2008 < 875    to the left,  improve=0.5527217, (0 missing)
##       age               < 79.5   to the left,  improve=0.4583429, (0 missing)
##       depression        < 0.5    to the right, improve=0.4287322, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1222173, (0 missing)
## 
## Node number 2950: 8 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.0004
##     class counts:     6     1     0     1     0
##    probabilities: 0.750 0.125 0.000 0.125 0.000 
## 
## Node number 2951: 20 observations,    complexity param=6.519188e-05
##   predicted class=B2  expected loss=0.6  P(node) =0.001
##     class counts:     7     8     4     1     0
##    probabilities: 0.350 0.400 0.200 0.050 0.000 
##   left son=5902 (7 obs) right son=5903 (13 obs)
##   Primary splits:
##       age               < 66.5   to the left,  improve=0.3131868, (0 missing)
##       reimbursement2008 < 770    to the left,  improve=0.3131868, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 805    to the right, agree=0.85, adj=0.571, (0 split)
## 
## Node number 3026: 14 observations
##   predicted class=B1  expected loss=0.07142857  P(node) =0.0007
##     class counts:    13     1     0     0     0
##    probabilities: 0.929 0.071 0.000 0.000 0.000 
## 
## Node number 3027: 125 observations,    complexity param=6.084576e-05
##   predicted class=B1  expected loss=0.344  P(node) =0.00625
##     class counts:    82    30    12     0     1
##    probabilities: 0.656 0.240 0.096 0.000 0.008 
##   left son=6054 (10 obs) right son=6055 (115 obs)
##   Primary splits:
##       arthritis         < 0.5    to the right, improve=0.9610435, (0 missing)
##       kidney            < 0.5    to the right, improve=0.8457324, (0 missing)
##       age               < 73.5   to the right, improve=0.7907549, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6473119, (0 missing)
##       reimbursement2008 < 925    to the right, improve=0.5392281, (0 missing)
## 
## Node number 3028: 9 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.00045
##     class counts:     4     5     0     0     0
##    probabilities: 0.444 0.556 0.000 0.000 0.000 
## 
## Node number 3029: 59 observations
##   predicted class=B1  expected loss=0.3050847  P(node) =0.00295
##     class counts:    41     8     5     5     0
##    probabilities: 0.695 0.136 0.085 0.085 0.000 
## 
## Node number 3030: 20 observations
##   predicted class=B1  expected loss=0.45  P(node) =0.001
##     class counts:    11     7     1     1     0
##    probabilities: 0.550 0.350 0.050 0.050 0.000 
## 
## Node number 3031: 9 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.00045
##     class counts:     3     5     1     0     0
##    probabilities: 0.333 0.556 0.111 0.000 0.000 
## 
## Node number 3046: 31 observations
##   predicted class=B1  expected loss=0.4516129  P(node) =0.00155
##     class counts:    17     5     7     2     0
##    probabilities: 0.548 0.161 0.226 0.065 0.000 
## 
## Node number 3047: 25 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.48  P(node) =0.00125
##     class counts:     8    13     4     0     0
##    probabilities: 0.320 0.520 0.160 0.000 0.000 
##   left son=6094 (18 obs) right son=6095 (7 obs)
##   Primary splits:
##       reimbursement2008 < 1435   to the left,  improve=2.7225400, (0 missing)
##       age               < 74.5   to the left,  improve=0.3782353, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.3316667, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.2463492, (0 missing)
##   Surrogate splits:
##       age < 75.5   to the left,  agree=0.76, adj=0.143, (0 split)
## 
## Node number 3072: 40 observations
##   predicted class=B1  expected loss=0.175  P(node) =0.002
##     class counts:    33     3     4     0     0
##    probabilities: 0.825 0.075 0.100 0.000 0.000 
## 
## Node number 3073: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     3     0     4     0     0
##    probabilities: 0.429 0.000 0.571 0.000 0.000 
## 
## Node number 3076: 23 observations
##   predicted class=B1  expected loss=0.2173913  P(node) =0.00115
##     class counts:    18     3     1     1     0
##    probabilities: 0.783 0.130 0.043 0.043 0.000 
## 
## Node number 3077: 69 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3768116  P(node) =0.00345
##     class counts:    43    19     6     0     1
##    probabilities: 0.623 0.275 0.087 0.000 0.014 
##   left son=6154 (59 obs) right son=6155 (10 obs)
##   Primary splits:
##       reimbursement2008 < 2295   to the left,  improve=0.9161385, (0 missing)
##       age               < 47     to the right, improve=0.6125604, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.4294916, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2435600, (0 missing)
## 
## Node number 3084: 58 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.4137931  P(node) =0.0029
##     class counts:    34    20     4     0     0
##    probabilities: 0.586 0.345 0.069 0.000 0.000 
##   left son=6168 (49 obs) right son=6169 (9 obs)
##   Primary splits:
##       reimbursement2008 < 2415   to the left,  improve=0.73782160, (0 missing)
##       age               < 77.5   to the right, improve=0.37655170, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.12048330, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.03843207, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.01005232, (0 missing)
##   Surrogate splits:
##       copd < 0.5    to the left,  agree=0.879, adj=0.222, (0 split)
## 
## Node number 3085: 14 observations
##   predicted class=B1  expected loss=0.3571429  P(node) =0.0007
##     class counts:     9     1     2     2     0
##    probabilities: 0.643 0.071 0.143 0.143 0.000 
## 
## Node number 3086: 7 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.00035
##     class counts:     5     1     0     1     0
##    probabilities: 0.714 0.143 0.000 0.143 0.000 
## 
## Node number 3087: 21 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.7142857  P(node) =0.00105
##     class counts:     6     6     5     4     0
##    probabilities: 0.286 0.286 0.238 0.190 0.000 
##   left son=6174 (13 obs) right son=6175 (8 obs)
##   Primary splits:
##       reimbursement2008 < 2170   to the left,  improve=0.7921245, (0 missing)
##       age               < 84.5   to the right, improve=0.6190476, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3412698, (0 missing)
##   Surrogate splits:
##       age        < 82.5   to the right, agree=0.762, adj=0.375, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.667, adj=0.125, (0 split)
## 
## Node number 3112: 30 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0015
##     class counts:    20    10     0     0     0
##    probabilities: 0.667 0.333 0.000 0.000 0.000 
##   left son=6224 (23 obs) right son=6225 (7 obs)
##   Primary splits:
##       age               < 77.5   to the left,  improve=2.6501040, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.1111110, (0 missing)
##       reimbursement2008 < 2885   to the left,  improve=0.6625259, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.0297619, (0 missing)
## 
## Node number 3113: 11 observations
##   predicted class=B2  expected loss=0.3636364  P(node) =0.00055
##     class counts:     4     7     0     0     0
##    probabilities: 0.364 0.636 0.000 0.000 0.000 
## 
## Node number 3114: 18 observations
##   predicted class=B1  expected loss=0.2777778  P(node) =0.0009
##     class counts:    13     2     3     0     0
##    probabilities: 0.722 0.111 0.167 0.000 0.000 
## 
## Node number 3115: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     2     4     0     0     1
##    probabilities: 0.286 0.571 0.000 0.000 0.143 
## 
## Node number 3162: 17 observations
##   predicted class=B1  expected loss=0.4705882  P(node) =0.00085
##     class counts:     9     5     1     2     0
##    probabilities: 0.529 0.294 0.059 0.118 0.000 
## 
## Node number 3163: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     1     4     0     2     0
##    probabilities: 0.143 0.571 0.000 0.286 0.000 
## 
## Node number 3180: 8 observations
##   predicted class=B1  expected loss=0.125  P(node) =0.0004
##     class counts:     7     0     0     1     0
##    probabilities: 0.875 0.000 0.000 0.125 0.000 
## 
## Node number 3181: 105 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5809524  P(node) =0.00525
##     class counts:    44    37    21     2     1
##    probabilities: 0.419 0.352 0.200 0.019 0.010 
##   left son=6362 (45 obs) right son=6363 (60 obs)
##   Primary splits:
##       age               < 75.5   to the right, improve=1.0650790, (0 missing)
##       reimbursement2008 < 2955   to the left,  improve=0.9904762, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7462449, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.7161905, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6605234, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1930   to the left,  agree=0.610, adj=0.089, (0 split)
##       arthritis         < 0.5    to the right, agree=0.581, adj=0.022, (0 split)
## 
## Node number 3332: 70 observations
##   predicted class=B1  expected loss=0.3  P(node) =0.0035
##     class counts:    49    12     5     3     1
##    probabilities: 0.700 0.171 0.071 0.043 0.014 
## 
## Node number 3333: 16 observations
##   predicted class=B2  expected loss=0.5625  P(node) =0.0008
##     class counts:     6     7     2     1     0
##    probabilities: 0.375 0.438 0.125 0.062 0.000 
## 
## Node number 3334: 8 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.0004
##     class counts:     6     1     1     0     0
##    probabilities: 0.750 0.125 0.125 0.000 0.000 
## 
## Node number 3335: 50 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.54  P(node) =0.0025
##     class counts:    23    23     2     2     0
##    probabilities: 0.460 0.460 0.040 0.040 0.000 
##   left son=6670 (42 obs) right son=6671 (8 obs)
##   Primary splits:
##       age               < 89.5   to the left,  improve=0.7633333, (0 missing)
##       reimbursement2008 < 2305   to the left,  improve=0.5728571, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.4736508, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3203509, (0 missing)
##       kidney            < 0.5    to the right, improve=0.1300000, (0 missing)
## 
## Node number 3340: 33 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.4242424  P(node) =0.00165
##     class counts:    19    10     3     0     1
##    probabilities: 0.576 0.303 0.091 0.000 0.030 
##   left son=6680 (19 obs) right son=6681 (14 obs)
##   Primary splits:
##       age               < 77.5   to the right, improve=2.15584400, (0 missing)
##       reimbursement2008 < 1845   to the right, improve=0.38814230, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.37012990, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.22177820, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.03282828, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1690   to the right, agree=0.636, adj=0.143, (0 split)
## 
## Node number 3341: 30 observations,    complexity param=0.000190143
##   predicted class=B2  expected loss=0.4333333  P(node) =0.0015
##     class counts:    12    17     1     0     0
##    probabilities: 0.400 0.567 0.033 0.000 0.000 
##   left son=6682 (12 obs) right son=6683 (18 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=1.1444440, (0 missing)
##       reimbursement2008 < 2375   to the right, improve=0.9651515, (0 missing)
##       age               < 83     to the left,  improve=0.7188537, (0 missing)
##       kidney            < 0.5    to the right, improve=0.6015152, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.1469697, (0 missing)
## 
## Node number 3342: 10 observations
##   predicted class=B1  expected loss=0.2  P(node) =0.0005
##     class counts:     8     0     1     1     0
##    probabilities: 0.800 0.000 0.100 0.100 0.000 
## 
## Node number 3343: 15 observations
##   predicted class=B2  expected loss=0.6  P(node) =0.00075
##     class counts:     4     6     1     4     0
##    probabilities: 0.267 0.400 0.067 0.267 0.000 
## 
## Node number 3344: 211 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.3791469  P(node) =0.01055
##     class counts:   131    51    18    10     1
##    probabilities: 0.621 0.242 0.085 0.047 0.005 
##   left son=6688 (96 obs) right son=6689 (115 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=1.4607100, (0 missing)
##       reimbursement2008 < 1735   to the left,  improve=1.3331950, (0 missing)
##       age               < 70.5   to the left,  improve=1.0529550, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.7906734, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3086469, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2375   to the right, agree=0.564, adj=0.042, (0 split)
##       age               < 69.5   to the left,  agree=0.559, adj=0.031, (0 split)
##       cancer            < 0.5    to the right, agree=0.559, adj=0.031, (0 split)
## 
## Node number 3345: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     2     5     0     0     0
##    probabilities: 0.286 0.714 0.000 0.000 0.000 
## 
## Node number 3348: 18 observations
##   predicted class=B1  expected loss=0.5555556  P(node) =0.0009
##     class counts:     8     5     2     3     0
##    probabilities: 0.444 0.278 0.111 0.167 0.000 
## 
## Node number 3349: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     1     5     1     1     0
##    probabilities: 0.125 0.625 0.125 0.125 0.000 
## 
## Node number 3352: 98 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5714286  P(node) =0.0049
##     class counts:    41    42     6     8     1
##    probabilities: 0.418 0.429 0.061 0.082 0.010 
##   left son=6704 (88 obs) right son=6705 (10 obs)
##   Primary splits:
##       reimbursement2008 < 2165   to the left,  improve=1.2299630, (0 missing)
##       age               < 72.5   to the left,  improve=0.8171297, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.7814001, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5288983, (0 missing)
##       cancer            < 0.5    to the right, improve=0.4885488, (0 missing)
## 
## Node number 3353: 17 observations
##   predicted class=B1  expected loss=0.5882353  P(node) =0.00085
##     class counts:     7     4     5     0     1
##    probabilities: 0.412 0.235 0.294 0.000 0.059 
## 
## Node number 3354: 23 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.6086957  P(node) =0.00115
##     class counts:     8     9     6     0     0
##    probabilities: 0.348 0.391 0.261 0.000 0.000 
##   left son=6708 (16 obs) right son=6709 (7 obs)
##   Primary splits:
##       reimbursement2008 < 2305   to the right, improve=0.9697205, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.3880105, (0 missing)
##       age               < 70.5   to the right, improve=0.3150502, (0 missing)
## 
## Node number 3355: 8 observations
##   predicted class=B2  expected loss=0.25  P(node) =0.0004
##     class counts:     0     6     2     0     0
##    probabilities: 0.000 0.750 0.250 0.000 0.000 
## 
## Node number 3358: 8 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0004
##     class counts:     4     1     1     2     0
##    probabilities: 0.500 0.125 0.125 0.250 0.000 
## 
## Node number 3359: 17 observations
##   predicted class=B3  expected loss=0.5294118  P(node) =0.00085
##     class counts:     5     2     8     1     1
##    probabilities: 0.294 0.118 0.471 0.059 0.059 
## 
## Node number 3424: 28 observations
##   predicted class=B1  expected loss=0.2142857  P(node) =0.0014
##     class counts:    22     1     2     2     1
##    probabilities: 0.786 0.036 0.071 0.071 0.036 
## 
## Node number 3425: 34 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.4117647  P(node) =0.0017
##     class counts:    20    10     2     2     0
##    probabilities: 0.588 0.294 0.059 0.059 0.000 
##   left son=6850 (10 obs) right son=6851 (24 obs)
##   Primary splits:
##       reimbursement2008 < 1865   to the right, improve=1.9088240, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.1388240, (0 missing)
##       age               < 65.5   to the right, improve=1.0445380, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.4073084, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3640867, (0 missing)
##   Surrogate splits:
##       age < 37.5   to the left,  agree=0.765, adj=0.2, (0 split)
## 
## Node number 3428: 25 observations
##   predicted class=B1  expected loss=0.44  P(node) =0.00125
##     class counts:    14     7     3     1     0
##    probabilities: 0.560 0.280 0.120 0.040 0.000 
## 
## Node number 3429: 29 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6551724  P(node) =0.00145
##     class counts:     7    10     9     3     0
##    probabilities: 0.241 0.345 0.310 0.103 0.000 
##   left son=6858 (22 obs) right son=6859 (7 obs)
##   Primary splits:
##       age               < 55     to the right, improve=1.5638150, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.2323050, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.9144648, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.6007260, (0 missing)
##       reimbursement2008 < 2075   to the right, improve=0.5667015, (0 missing)
##   Surrogate splits:
##       kidney < 0.5    to the left,  agree=0.793, adj=0.143, (0 split)
## 
## Node number 3434: 10 observations
##   predicted class=B2  expected loss=0.2  P(node) =0.0005
##     class counts:     2     8     0     0     0
##    probabilities: 0.200 0.800 0.000 0.000 0.000 
## 
## Node number 3435: 99 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.4949495  P(node) =0.00495
##     class counts:    32    50    16     1     0
##    probabilities: 0.323 0.505 0.162 0.010 0.000 
##   left son=6870 (46 obs) right son=6871 (53 obs)
##   Primary splits:
##       reimbursement2008 < 2045   to the right, improve=1.4422070, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.6616256, (0 missing)
##       age               < 75.5   to the right, improve=0.5566090, (0 missing)
##       copd              < 0.5    to the right, improve=0.5057552, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.4451178, (0 missing)
##   Surrogate splits:
##       age          < 72.5   to the left,  agree=0.576, adj=0.087, (0 split)
##       diabetes     < 0.5    to the right, agree=0.566, adj=0.065, (0 split)
##       arthritis    < 0.5    to the right, agree=0.556, adj=0.043, (0 split)
##       kidney       < 0.5    to the right, agree=0.556, adj=0.043, (0 split)
##       osteoporosis < 0.5    to the right, agree=0.556, adj=0.043, (0 split)
## 
## Node number 3466: 14 observations
##   predicted class=B1  expected loss=0.2142857  P(node) =0.0007
##     class counts:    11     2     0     1     0
##    probabilities: 0.786 0.143 0.000 0.071 0.000 
## 
## Node number 3467: 55 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5090909  P(node) =0.00275
##     class counts:    27    17     8     3     0
##    probabilities: 0.491 0.309 0.145 0.055 0.000 
##   left son=6934 (41 obs) right son=6935 (14 obs)
##   Primary splits:
##       age               < 83.5   to the left,  improve=2.7071900, (0 missing)
##       reimbursement2008 < 2680   to the right, improve=1.7662000, (0 missing)
##       copd              < 0.5    to the left,  improve=1.5148270, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.3909091, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1531834, (0 missing)
## 
## Node number 3468: 58 observations,    complexity param=0.0001014096
##   predicted class=B1  expected loss=0.4310345  P(node) =0.0029
##     class counts:    33    11    10     2     2
##    probabilities: 0.569 0.190 0.172 0.034 0.034 
##   left son=6936 (7 obs) right son=6937 (51 obs)
##   Primary splits:
##       reimbursement2008 < 3325   to the right, improve=2.0209600, (0 missing)
##       age               < 70.5   to the right, improve=0.7361795, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.5862069, (0 missing)
##       kidney            < 0.5    to the right, improve=0.3220159, (0 missing)
##       copd              < 0.5    to the left,  improve=0.2258621, (0 missing)
## 
## Node number 3469: 46 observations,    complexity param=0.0002662002
##   predicted class=B2  expected loss=0.6086957  P(node) =0.0023
##     class counts:    17    18     9     2     0
##    probabilities: 0.370 0.391 0.196 0.043 0.000 
##   left son=6938 (33 obs) right son=6939 (13 obs)
##   Primary splits:
##       kidney            < 0.5    to the left,  improve=1.2037090, (0 missing)
##       age               < 81.5   to the right, improve=0.9942551, (0 missing)
##       reimbursement2008 < 2695   to the left,  improve=0.9260870, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7830762, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4167302, (0 missing)
##   Surrogate splits:
##       copd              < 0.5    to the left,  agree=0.783, adj=0.231, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.739, adj=0.077, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.739, adj=0.077, (0 split)
##       reimbursement2008 < 3385   to the left,  agree=0.739, adj=0.077, (0 split)
## 
## Node number 3490: 67 observations,    complexity param=0.000253524
##   predicted class=B1  expected loss=0.4626866  P(node) =0.00335
##     class counts:    36    18     6     7     0
##    probabilities: 0.537 0.269 0.090 0.104 0.000 
##   left son=6980 (23 obs) right son=6981 (44 obs)
##   Primary splits:
##       diabetes          < 0.5    to the left,  improve=1.7004600, (0 missing)
##       reimbursement2008 < 2850   to the right, improve=0.8931479, (0 missing)
##       age               < 87.5   to the right, improve=0.8361371, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5107368, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4996072, (0 missing)
##   Surrogate splits:
##       age    < 41.5   to the left,  agree=0.687, adj=0.087, (0 split)
##       stroke < 0.5    to the right, agree=0.672, adj=0.043, (0 split)
## 
## Node number 3491: 58 observations,    complexity param=0.0006084576
##   predicted class=B2  expected loss=0.5  P(node) =0.0029
##     class counts:    20    29     5     4     0
##    probabilities: 0.345 0.500 0.086 0.069 0.000 
##   left son=6982 (13 obs) right son=6983 (45 obs)
##   Primary splits:
##       age               < 67.5   to the left,  improve=1.9273210, (0 missing)
##       reimbursement2008 < 3285   to the right, improve=1.2543850, (0 missing)
##       depression        < 0.5    to the left,  improve=1.0681200, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6646677, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.3607892, (0 missing)
## 
## Node number 3502: 39 observations,    complexity param=0.0003549336
##   predicted class=B1  expected loss=0.6923077  P(node) =0.00195
##     class counts:    12    12     9     6     0
##    probabilities: 0.308 0.308 0.231 0.154 0.000 
##   left son=7004 (19 obs) right son=7005 (20 obs)
##   Primary splits:
##       reimbursement2008 < 3120   to the right, improve=1.4732790, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=1.0783480, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7169889, (0 missing)
##       age               < 79.5   to the left,  improve=0.6923077, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6923077, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the right, agree=0.795, adj=0.579, (0 split)
##       depression < 0.5    to the right, agree=0.641, adj=0.263, (0 split)
##       age        < 79.5   to the left,  agree=0.615, adj=0.211, (0 split)
##       diabetes   < 0.5    to the left,  agree=0.615, adj=0.211, (0 split)
##       copd       < 0.5    to the right, agree=0.590, adj=0.158, (0 split)
## 
## Node number 3503: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     0     2     4     1     0
##    probabilities: 0.000 0.286 0.571 0.143 0.000 
## 
## Node number 3520: 40 observations,    complexity param=0.0002788764
##   predicted class=B1  expected loss=0.55  P(node) =0.002
##     class counts:    18    15     5     1     1
##    probabilities: 0.450 0.375 0.125 0.025 0.025 
##   left son=7040 (32 obs) right son=7041 (8 obs)
##   Primary splits:
##       age          < 80.5   to the left,  improve=1.4125000, (0 missing)
##       osteoporosis < 0.5    to the left,  improve=1.0583330, (0 missing)
##       copd         < 0.5    to the left,  improve=0.8022792, (0 missing)
##       depression   < 0.5    to the left,  improve=0.7111111, (0 missing)
##       diabetes     < 0.5    to the left,  improve=0.2933333, (0 missing)
## 
## Node number 3521: 64 observations,    complexity param=0.0002788764
##   predicted class=B2  expected loss=0.5  P(node) =0.0032
##     class counts:    20    32     9     3     0
##    probabilities: 0.312 0.500 0.141 0.047 0.000 
##   left son=7042 (52 obs) right son=7043 (12 obs)
##   Primary splits:
##       reimbursement2008 < 2565   to the right, improve=1.3052880, (0 missing)
##       age               < 72     to the right, improve=1.1374010, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6240303, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.4687500, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.4238501, (0 missing)
## 
## Node number 3522: 12 observations
##   predicted class=B2  expected loss=0.4166667  P(node) =0.0006
##     class counts:     4     7     1     0     0
##    probabilities: 0.333 0.583 0.083 0.000 0.000 
## 
## Node number 3523: 26 observations,    complexity param=0.0001521144
##   predicted class=B3  expected loss=0.5384615  P(node) =0.0013
##     class counts:     7     7    12     0     0
##    probabilities: 0.269 0.269 0.462 0.000 0.000 
##   left son=7046 (19 obs) right son=7047 (7 obs)
##   Primary splits:
##       diabetes          < 0.5    to the right, improve=2.3464430, (0 missing)
##       copd              < 0.5    to the left,  improve=1.3088490, (0 missing)
##       reimbursement2008 < 2640   to the right, improve=1.3088490, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.9423077, (0 missing)
##       age               < 68     to the left,  improve=0.7707391, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2620   to the right, agree=0.885, adj=0.571, (0 split)
##       copd              < 0.5    to the left,  agree=0.769, adj=0.143, (0 split)
## 
## Node number 3554: 11 observations
##   predicted class=B1  expected loss=0.1818182  P(node) =0.00055
##     class counts:     9     2     0     0     0
##    probabilities: 0.818 0.182 0.000 0.000 0.000 
## 
## Node number 3555: 18 observations
##   predicted class=B2  expected loss=0.6111111  P(node) =0.0009
##     class counts:     5     7     4     1     1
##    probabilities: 0.278 0.389 0.222 0.056 0.056 
## 
## Node number 3590: 23 observations
##   predicted class=B1  expected loss=0.3913043  P(node) =0.00115
##     class counts:    14     6     2     1     0
##    probabilities: 0.609 0.261 0.087 0.043 0.000 
## 
## Node number 3591: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     2     4     1     0     0
##    probabilities: 0.286 0.571 0.143 0.000 0.000 
## 
## Node number 3594: 56 observations
##   predicted class=B1  expected loss=0.375  P(node) =0.0028
##     class counts:    35    15     3     2     1
##    probabilities: 0.625 0.268 0.054 0.036 0.018 
## 
## Node number 3595: 11 observations
##   predicted class=B2  expected loss=0.6363636  P(node) =0.00055
##     class counts:     3     4     3     1     0
##    probabilities: 0.273 0.364 0.273 0.091 0.000 
## 
## Node number 3596: 8 observations
##   predicted class=B1  expected loss=0.125  P(node) =0.0004
##     class counts:     7     1     0     0     0
##    probabilities: 0.875 0.125 0.000 0.000 0.000 
## 
## Node number 3597: 97 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.4639175  P(node) =0.00485
##     class counts:    52    26    17     2     0
##    probabilities: 0.536 0.268 0.175 0.021 0.000 
##   left son=7194 (79 obs) right son=7195 (18 obs)
##   Primary splits:
##       age               < 81.5   to the left,  improve=2.2155960, (0 missing)
##       reimbursement2008 < 5125   to the right, improve=1.6287330, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8331981, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.7669320, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.2559504, (0 missing)
## 
## Node number 3610: 22 observations
##   predicted class=B2  expected loss=0.4090909  P(node) =0.0011
##     class counts:     7    13     1     1     0
##    probabilities: 0.318 0.591 0.045 0.045 0.000 
## 
## Node number 3611: 12 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0006
##     class counts:     6     3     2     1     0
##    probabilities: 0.500 0.250 0.167 0.083 0.000 
## 
## Node number 3644: 7 observations
##   predicted class=B2  expected loss=0.1428571  P(node) =0.00035
##     class counts:     1     6     0     0     0
##    probabilities: 0.143 0.857 0.000 0.000 0.000 
## 
## Node number 3645: 15 observations
##   predicted class=B1  expected loss=0.6  P(node) =0.00075
##     class counts:     6     5     3     1     0
##    probabilities: 0.400 0.333 0.200 0.067 0.000 
## 
## Node number 3646: 9 observations
##   predicted class=B1  expected loss=0.5555556  P(node) =0.00045
##     class counts:     4     3     1     1     0
##    probabilities: 0.444 0.333 0.111 0.111 0.000 
## 
## Node number 3647: 23 observations
##   predicted class=B3  expected loss=0.4782609  P(node) =0.00115
##     class counts:     7     4    12     0     0
##    probabilities: 0.304 0.174 0.522 0.000 0.000 
## 
## Node number 3750: 13 observations
##   predicted class=B2  expected loss=0.1538462  P(node) =0.00065
##     class counts:     2    11     0     0     0
##    probabilities: 0.154 0.846 0.000 0.000 0.000 
## 
## Node number 3751: 25 observations,    complexity param=7.60572e-05
##   predicted class=B2  expected loss=0.48  P(node) =0.00125
##     class counts:     6    13     4     2     0
##    probabilities: 0.240 0.520 0.160 0.080 0.000 
##   left son=7502 (10 obs) right son=7503 (15 obs)
##   Primary splits:
##       reimbursement2008 < 5090   to the left,  improve=1.2666670, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.4558824, (0 missing)
##       age               < 71.5   to the left,  improve=0.3461538, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3174603, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.2500000, (0 missing)
##   Surrogate splits:
##       age       < 71.5   to the right, agree=0.72, adj=0.3, (0 split)
##       cancer    < 0.5    to the left,  agree=0.72, adj=0.3, (0 split)
##       arthritis < 0.5    to the right, agree=0.64, adj=0.1, (0 split)
## 
## Node number 3758: 25 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.52  P(node) =0.00125
##     class counts:     5    12     6     2     0
##    probabilities: 0.200 0.480 0.240 0.080 0.000 
##   left son=7516 (18 obs) right son=7517 (7 obs)
##   Primary splits:
##       reimbursement2008 < 19195  to the left,  improve=0.7828571, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=0.7828571, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.5733333, (0 missing)
##       age               < 71.5   to the right, improve=0.5370588, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.0374359, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the left,  agree=1.00, adj=1.000, (0 split)
##       cancer     < 0.5    to the left,  agree=0.80, adj=0.286, (0 split)
##       age        < 69.5   to the right, agree=0.76, adj=0.143, (0 split)
##       stroke     < 0.5    to the left,  agree=0.76, adj=0.143, (0 split)
## 
## Node number 3759: 14 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.0007
##     class counts:     4     1     8     1     0
##    probabilities: 0.286 0.071 0.571 0.071 0.000 
## 
## Node number 3824: 15 observations
##   predicted class=B1  expected loss=0.4666667  P(node) =0.00075
##     class counts:     8     4     3     0     0
##    probabilities: 0.533 0.267 0.200 0.000 0.000 
## 
## Node number 3825: 15 observations
##   predicted class=B2  expected loss=0.5333333  P(node) =0.00075
##     class counts:     3     7     2     3     0
##    probabilities: 0.200 0.467 0.133 0.200 0.000 
## 
## Node number 3840: 8 observations
##   predicted class=B1  expected loss=0.375  P(node) =0.0004
##     class counts:     5     2     1     0     0
##    probabilities: 0.625 0.250 0.125 0.000 0.000 
## 
## Node number 3841: 24 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4583333  P(node) =0.0012
##     class counts:    10    13     1     0     0
##    probabilities: 0.417 0.542 0.042 0.000 0.000 
##   left son=7682 (7 obs) right son=7683 (17 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=0.38025210, (0 missing)
##       reimbursement2008 < 6890   to the right, improve=0.35000000, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.17222220, (0 missing)
##       age               < 67.5   to the right, improve=0.12500000, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.02731092, (0 missing)
##   Surrogate splits:
##       age           < 66.5   to the left,  agree=0.75, adj=0.143, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.75, adj=0.143, (0 split)
## 
## Node number 3842: 19 observations
##   predicted class=B1  expected loss=0.2105263  P(node) =0.00095
##     class counts:    15     1     3     0     0
##    probabilities: 0.789 0.053 0.158 0.000 0.000 
## 
## Node number 3843: 104 observations,    complexity param=0.0003422574
##   predicted class=B1  expected loss=0.5480769  P(node) =0.0052
##     class counts:    47    31    23     3     0
##    probabilities: 0.452 0.298 0.221 0.029 0.000 
##   left son=7686 (76 obs) right son=7687 (28 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=2.6920190, (0 missing)
##       reimbursement2008 < 3815   to the left,  improve=2.1500750, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9947414, (0 missing)
##       age               < 45.5   to the left,  improve=0.6525368, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5917679, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4710   to the left,  agree=0.769, adj=0.143, (0 split)
##       stroke            < 0.5    to the left,  agree=0.740, adj=0.036, (0 split)
## 
## Node number 3848: 7 observations
##   predicted class=B1  expected loss=0.1428571  P(node) =0.00035
##     class counts:     6     1     0     0     0
##    probabilities: 0.857 0.143 0.000 0.000 0.000 
## 
## Node number 3849: 24 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5833333  P(node) =0.0012
##     class counts:     6    10     2     5     1
##    probabilities: 0.250 0.417 0.083 0.208 0.042 
##   left son=7698 (9 obs) right son=7699 (15 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=1.2611110, (0 missing)
##       age               < 58.5   to the left,  improve=1.2083330, (0 missing)
##       reimbursement2008 < 24480  to the left,  improve=0.9488796, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7083333, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3119048, (0 missing)
##   Surrogate splits:
##       age               < 50.5   to the left,  agree=0.708, adj=0.222, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.667, adj=0.111, (0 split)
##       reimbursement2008 < 19645  to the right, agree=0.667, adj=0.111, (0 split)
##       bucket2008        < 3.5    to the right, agree=0.667, adj=0.111, (0 split)
## 
## Node number 3850: 13 observations
##   predicted class=B3  expected loss=0.5384615  P(node) =0.00065
##     class counts:     2     3     6     2     0
##    probabilities: 0.154 0.231 0.462 0.154 0.000 
## 
## Node number 3851: 8 observations
##   predicted class=B4  expected loss=0.625  P(node) =0.0004
##     class counts:     2     2     1     3     0
##    probabilities: 0.250 0.250 0.125 0.375 0.000 
## 
## Node number 3856: 117 observations,    complexity param=0.0003295812
##   predicted class=B1  expected loss=0.4786325  P(node) =0.00585
##     class counts:    61    35    13     8     0
##    probabilities: 0.521 0.299 0.111 0.068 0.000 
##   left son=7712 (11 obs) right son=7713 (106 obs)
##   Primary splits:
##       reimbursement2008 < 5335   to the left,  improve=1.6681470, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.5859199, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5517094, (0 missing)
##       age               < 82.5   to the left,  improve=0.5042735, (0 missing)
##       copd              < 0.5    to the right, improve=0.4257959, (0 missing)
## 
## Node number 3857: 27 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.4814815  P(node) =0.00135
##     class counts:    10    14     2     1     0
##    probabilities: 0.370 0.519 0.074 0.037 0.000 
##   left son=7714 (13 obs) right son=7715 (14 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the right, improve=1.1925110, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.0740740, (0 missing)
##       reimbursement2008 < 8000   to the left,  improve=0.6980057, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.6980057, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3386940, (0 missing)
##   Surrogate splits:
##       alzheimers        < 0.5    to the left,  agree=0.667, adj=0.308, (0 split)
##       ihd               < 0.5    to the right, agree=0.593, adj=0.154, (0 split)
##       reimbursement2008 < 7825   to the right, agree=0.593, adj=0.154, (0 split)
##       bucket2008        < 3.5    to the right, agree=0.593, adj=0.154, (0 split)
##       age               < 71.5   to the right, agree=0.556, adj=0.077, (0 split)
## 
## Node number 3858: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     1     5     1     0     0
##    probabilities: 0.143 0.714 0.143 0.000 0.000 
## 
## Node number 3859: 19 observations
##   predicted class=B3  expected loss=0.6315789  P(node) =0.00095
##     class counts:     6     4     7     1     1
##    probabilities: 0.316 0.211 0.368 0.053 0.053 
## 
## Node number 3860: 17 observations
##   predicted class=B1  expected loss=0.2941176  P(node) =0.00085
##     class counts:    12     2     1     2     0
##    probabilities: 0.706 0.118 0.059 0.118 0.000 
## 
## Node number 3861: 11 observations
##   predicted class=B2  expected loss=0.3636364  P(node) =0.00055
##     class counts:     3     7     0     0     1
##    probabilities: 0.273 0.636 0.000 0.000 0.091 
## 
## Node number 3862: 61 observations,    complexity param=0.0004056384
##   predicted class=B2  expected loss=0.4262295  P(node) =0.00305
##     class counts:    14    35    10     2     0
##    probabilities: 0.230 0.574 0.164 0.033 0.000 
##   left son=7724 (14 obs) right son=7725 (47 obs)
##   Primary splits:
##       reimbursement2008 < 14285  to the right, improve=2.9027360, (0 missing)
##       age               < 81.5   to the left,  improve=2.7429190, (0 missing)
##       stroke            < 0.5    to the right, improve=0.7350427, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6774892, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.6382429, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.869, adj=0.429, (0 split)
## 
## Node number 3863: 68 observations,    complexity param=0.0004056384
##   predicted class=B2  expected loss=0.6617647  P(node) =0.0034
##     class counts:    20    23    16     8     1
##    probabilities: 0.294 0.338 0.235 0.118 0.015 
##   left son=7726 (49 obs) right son=7727 (19 obs)
##   Primary splits:
##       reimbursement2008 < 7090   to the right, improve=2.0709230, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.9533610, (0 missing)
##       stroke            < 0.5    to the left,  improve=1.8022620, (0 missing)
##       copd              < 0.5    to the left,  improve=1.4319330, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.9282531, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.926, adj=0.737, (0 split)
##       age        < 87.5   to the left,  agree=0.735, adj=0.053, (0 split)
## 
## Node number 3864: 50 observations
##   predicted class=B2  expected loss=0.3  P(node) =0.0025
##     class counts:    11    35     2     2     0
##    probabilities: 0.220 0.700 0.040 0.040 0.000 
## 
## Node number 3865: 14 observations
##   predicted class=B1  expected loss=0.5714286  P(node) =0.0007
##     class counts:     6     3     5     0     0
##    probabilities: 0.429 0.214 0.357 0.000 0.000 
## 
## Node number 3870: 37 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.6216216  P(node) =0.00185
##     class counts:    14    14     6     3     0
##    probabilities: 0.378 0.378 0.162 0.081 0.000 
##   left son=7740 (17 obs) right son=7741 (20 obs)
##   Primary splits:
##       reimbursement2008 < 4035   to the left,  improve=1.0186010, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6996787, (0 missing)
##       age               < 87.5   to the right, improve=0.6571379, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6256971, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.5308041, (0 missing)
##   Surrogate splits:
##       age           < 90.5   to the right, agree=0.595, adj=0.118, (0 split)
##       copd          < 0.5    to the left,  agree=0.595, adj=0.118, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.568, adj=0.059, (0 split)
## 
## Node number 3871: 67 observations
##   predicted class=B2  expected loss=0.4179104  P(node) =0.00335
##     class counts:    14    39    12     2     0
##    probabilities: 0.209 0.582 0.179 0.030 0.000 
## 
## Node number 3892: 16 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0008
##     class counts:     8     4     2     2     0
##    probabilities: 0.500 0.250 0.125 0.125 0.000 
## 
## Node number 3893: 33 observations,    complexity param=0.0004563432
##   predicted class=B3  expected loss=0.5757576  P(node) =0.00165
##     class counts:     8     9    14     2     0
##    probabilities: 0.242 0.273 0.424 0.061 0.000 
##   left son=7786 (11 obs) right son=7787 (22 obs)
##   Primary splits:
##       reimbursement2008 < 5825   to the left,  improve=2.0909090, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.5680110, (0 missing)
##       age               < 66.5   to the right, improve=1.4575420, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.3232320, (0 missing)
##       depression        < 0.5    to the left,  improve=0.8073593, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.788, adj=0.364, (0 split)
##       ihd        < 0.5    to the left,  agree=0.758, adj=0.273, (0 split)
## 
## Node number 3894: 33 observations,    complexity param=7.60572e-05
##   predicted class=B3  expected loss=0.5757576  P(node) =0.00165
##     class counts:     7     9    14     3     0
##    probabilities: 0.212 0.273 0.424 0.091 0.000 
##   left son=7788 (26 obs) right son=7789 (7 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=1.4748580, (0 missing)
##       copd              < 0.5    to the left,  improve=1.3210120, (0 missing)
##       reimbursement2008 < 14730  to the left,  improve=0.7056277, (0 missing)
##       age               < 76.5   to the right, improve=0.6905901, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5151515, (0 missing)
## 
## Node number 3895: 30 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4333333  P(node) =0.0015
##     class counts:     1    17     8     4     0
##    probabilities: 0.033 0.567 0.267 0.133 0.000 
##   left son=7790 (13 obs) right son=7791 (17 obs)
##   Primary splits:
##       age               < 75.5   to the left,  improve=2.7164400, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.2202380, (0 missing)
##       reimbursement2008 < 6230   to the left,  improve=1.0828160, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.6236045, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4896332, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4310   to the left,  agree=0.700, adj=0.308, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.667, adj=0.231, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.600, adj=0.077, (0 split)
##       stroke            < 0.5    to the right, agree=0.600, adj=0.077, (0 split)
## 
## Node number 3936: 30 observations
##   predicted class=B1  expected loss=0.4333333  P(node) =0.0015
##     class counts:    17    10     1     1     1
##    probabilities: 0.567 0.333 0.033 0.033 0.033 
## 
## Node number 3937: 8 observations
##   predicted class=B4  expected loss=0.625  P(node) =0.0004
##     class counts:     2     2     1     3     0
##    probabilities: 0.250 0.250 0.125 0.375 0.000 
## 
## Node number 3940: 59 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.4915254  P(node) =0.00295
##     class counts:    19    30     6     3     1
##    probabilities: 0.322 0.508 0.102 0.051 0.017 
##   left son=7880 (7 obs) right son=7881 (52 obs)
##   Primary splits:
##       reimbursement2008 < 4180   to the left,  improve=2.3199850, (0 missing)
##       age               < 74.5   to the right, improve=1.6846670, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7680925, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4469662, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.3751074, (0 missing)
## 
## Node number 3941: 26 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.6923077  P(node) =0.0013
##     class counts:     8     8     5     5     0
##    probabilities: 0.308 0.308 0.192 0.192 0.000 
##   left son=7882 (18 obs) right son=7883 (8 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=1.5705130, (0 missing)
##       age               < 90.5   to the right, improve=1.5147480, (0 missing)
##       reimbursement2008 < 5065   to the left,  improve=1.3038460, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5586081, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5072296, (0 missing)
##   Surrogate splits:
##       copd < 0.5    to the left,  agree=0.731, adj=0.125, (0 split)
## 
## Node number 3942: 32 observations
##   predicted class=B2  expected loss=0.34375  P(node) =0.0016
##     class counts:     1    21     4     6     0
##    probabilities: 0.031 0.656 0.125 0.187 0.000 
## 
## Node number 3943: 10 observations
##   predicted class=B1  expected loss=0.7  P(node) =0.0005
##     class counts:     3     2     2     3     0
##    probabilities: 0.300 0.200 0.200 0.300 0.000 
## 
## Node number 3946: 10 observations
##   predicted class=B2  expected loss=0.4  P(node) =0.0005
##     class counts:     2     6     0     2     0
##    probabilities: 0.200 0.600 0.000 0.200 0.000 
## 
## Node number 3947: 11 observations
##   predicted class=B4  expected loss=0.5454545  P(node) =0.00055
##     class counts:     2     3     1     5     0
##    probabilities: 0.182 0.273 0.091 0.455 0.000 
## 
## Node number 3950: 23 observations
##   predicted class=B2  expected loss=0.3043478  P(node) =0.00115
##     class counts:     2    16     3     2     0
##    probabilities: 0.087 0.696 0.130 0.087 0.000 
## 
## Node number 3951: 22 observations,    complexity param=0.0001521144
##   predicted class=B3  expected loss=0.5  P(node) =0.0011
##     class counts:     3     8    11     0     0
##    probabilities: 0.136 0.364 0.500 0.000 0.000 
##   left son=7902 (15 obs) right son=7903 (7 obs)
##   Primary splits:
##       reimbursement2008 < 6650   to the right, improve=2.0008660, (0 missing)
##       copd              < 0.5    to the right, improve=1.9246750, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.7630150, (0 missing)
##       age               < 72.5   to the left,  improve=0.9722944, (0 missing)
##   Surrogate splits:
##       age           < 64.5   to the right, agree=0.727, adj=0.143, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.727, adj=0.143, (0 split)
##       ihd           < 0.5    to the right, agree=0.727, adj=0.143, (0 split)
##       stroke        < 0.5    to the left,  agree=0.727, adj=0.143, (0 split)
## 
## Node number 3956: 52 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.4230769  P(node) =0.0026
##     class counts:     8    30    10     4     0
##    probabilities: 0.154 0.577 0.192 0.077 0.000 
##   left son=7912 (30 obs) right son=7913 (22 obs)
##   Primary splits:
##       reimbursement2008 < 23850  to the left,  improve=3.0974360, (0 missing)
##       age               < 77.5   to the right, improve=1.7192480, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=1.1057690, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8778281, (0 missing)
##       cancer            < 0.5    to the right, improve=0.6335470, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the left,  agree=0.731, adj=0.364, (0 split)
##       cancer     < 0.5    to the left,  agree=0.615, adj=0.091, (0 split)
##       age        < 59     to the right, agree=0.596, adj=0.045, (0 split)
##       stroke     < 0.5    to the left,  agree=0.596, adj=0.045, (0 split)
## 
## Node number 3957: 164 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5853659  P(node) =0.0082
##     class counts:    34    68    46    14     2
##    probabilities: 0.207 0.415 0.280 0.085 0.012 
##   left son=7914 (90 obs) right son=7915 (74 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=1.4857980, (0 missing)
##       reimbursement2008 < 4235   to the right, improve=1.2625250, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.1619200, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.0523830, (0 missing)
##       age               < 89.5   to the right, improve=0.8063318, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 9795   to the left,  agree=0.604, adj=0.122, (0 split)
##       copd              < 0.5    to the left,  agree=0.598, adj=0.108, (0 split)
##       age               < 85.5   to the left,  agree=0.585, adj=0.081, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.585, adj=0.081, (0 split)
##       ihd               < 0.5    to the right, agree=0.579, adj=0.068, (0 split)
## 
## Node number 3968: 11 observations
##   predicted class=B1  expected loss=0.2727273  P(node) =0.00055
##     class counts:     8     0     3     0     0
##    probabilities: 0.727 0.000 0.273 0.000 0.000 
## 
## Node number 3969: 32 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.6875  P(node) =0.0016
##     class counts:    10     9     9     2     2
##    probabilities: 0.312 0.281 0.281 0.062 0.062 
##   left son=7938 (24 obs) right son=7939 (8 obs)
##   Primary splits:
##       age               < 96.5   to the left,  improve=1.8958330, (0 missing)
##       copd              < 0.5    to the right, improve=1.4291670, (0 missing)
##       reimbursement2008 < 10790  to the right, improve=0.8539286, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6875000, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3878968, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 10790  to the right, agree=0.781, adj=0.125, (0 split)
## 
## Node number 3970: 8 observations
##   predicted class=B2  expected loss=0.25  P(node) =0.0004
##     class counts:     0     6     2     0     0
##    probabilities: 0.000 0.750 0.250 0.000 0.000 
## 
## Node number 3971: 16 observations
##   predicted class=B3  expected loss=0.5625  P(node) =0.0008
##     class counts:     4     3     7     2     0
##    probabilities: 0.250 0.188 0.438 0.125 0.000 
## 
## Node number 3974: 177 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6101695  P(node) =0.00885
##     class counts:    46    69    25    32     5
##    probabilities: 0.260 0.390 0.141 0.181 0.028 
##   left son=7948 (169 obs) right son=7949 (8 obs)
##   Primary splits:
##       reimbursement2008 < 14365  to the left,  improve=2.4954790, (0 missing)
##       age               < 75.5   to the right, improve=1.9376320, (0 missing)
##       stroke            < 0.5    to the right, improve=0.7544507, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.6832293, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.5905001, (0 missing)
## 
## Node number 3975: 91 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6483516  P(node) =0.00455
##     class counts:    14    32    24    18     3
##    probabilities: 0.154 0.352 0.264 0.198 0.033 
##   left son=7950 (34 obs) right son=7951 (57 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=1.981073, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.924030, (0 missing)
##       depression        < 0.5    to the left,  improve=1.545458, (0 missing)
##       reimbursement2008 < 9695   to the right, improve=1.218681, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.168681, (0 missing)
##   Surrogate splits:
##       ihd < 0.5    to the left,  agree=0.67, adj=0.118, (0 split)
## 
## Node number 3980: 210 observations,    complexity param=0.0003650745
##   predicted class=B2  expected loss=0.6047619  P(node) =0.0105
##     class counts:    44    83    47    31     5
##    probabilities: 0.210 0.395 0.224 0.148 0.024 
##   left son=7960 (48 obs) right son=7961 (162 obs)
##   Primary splits:
##       age               < 81.5   to the right, improve=1.422399, (0 missing)
##       ihd               < 0.5    to the right, improve=1.305861, (0 missing)
##       reimbursement2008 < 4080   to the left,  improve=1.052847, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.007552, (0 missing)
##       depression        < 0.5    to the right, improve=0.922645, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 6050   to the right, agree=0.776, adj=0.021, (0 split)
## 
## Node number 3981: 25 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.52  P(node) =0.00125
##     class counts:     1    10    12     1     1
##    probabilities: 0.040 0.400 0.480 0.040 0.040 
##   left son=7962 (17 obs) right son=7963 (8 obs)
##   Primary splits:
##       reimbursement2008 < 6260   to the right, improve=1.3258820, (0 missing)
##       age               < 67.5   to the right, improve=0.7073016, (0 missing)
##       depression        < 0.5    to the right, improve=0.4661538, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4576623, (0 missing)
##       copd              < 0.5    to the right, improve=0.2588889, (0 missing)
##   Surrogate splits:
##       age < 75     to the left,  agree=0.72, adj=0.125, (0 split)
## 
## Node number 4008: 19 observations
##   predicted class=B2  expected loss=0.2631579  P(node) =0.00095
##     class counts:     2    14     1     2     0
##    probabilities: 0.105 0.737 0.053 0.105 0.000 
## 
## Node number 4009: 69 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.4782609  P(node) =0.00345
##     class counts:    14    36    13     5     1
##    probabilities: 0.203 0.522 0.188 0.072 0.014 
##   left son=8018 (29 obs) right son=8019 (40 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=1.4558970, (0 missing)
##       age               < 81.5   to the right, improve=1.2755920, (0 missing)
##       reimbursement2008 < 3895   to the left,  improve=1.2388600, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6811594, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6025765, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 3955   to the left,  agree=0.667, adj=0.207, (0 split)
##       age               < 93     to the right, agree=0.623, adj=0.103, (0 split)
##       depression        < 0.5    to the right, agree=0.623, adj=0.103, (0 split)
## 
## Node number 4024: 13 observations
##   predicted class=B2  expected loss=0.5384615  P(node) =0.00065
##     class counts:     3     6     2     2     0
##    probabilities: 0.231 0.462 0.154 0.154 0.000 
## 
## Node number 4025: 22 observations
##   predicted class=B3  expected loss=0.5454545  P(node) =0.0011
##     class counts:     4     5    10     3     0
##    probabilities: 0.182 0.227 0.455 0.136 0.000 
## 
## Node number 4026: 187 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5347594  P(node) =0.00935
##     class counts:    20    87    53    22     5
##    probabilities: 0.107 0.465 0.283 0.118 0.027 
##   left son=8052 (35 obs) right son=8053 (152 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=0.9804330, (0 missing)
##       reimbursement2008 < 7580   to the right, improve=0.9500758, (0 missing)
##       age               < 75.5   to the left,  improve=0.9208236, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8858296, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.6009844, (0 missing)
## 
## Node number 4027: 31 observations
##   predicted class=B2  expected loss=0.4516129  P(node) =0.00155
##     class counts:     2    17     4     8     0
##    probabilities: 0.065 0.548 0.129 0.258 0.000 
## 
## Node number 4064: 59 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.6610169  P(node) =0.00295
##     class counts:    20    12    12    15     0
##    probabilities: 0.339 0.203 0.203 0.254 0.000 
##   left son=8128 (10 obs) right son=8129 (49 obs)
##   Primary splits:
##       stroke            < 0.5    to the right, improve=2.0111380, (0 missing)
##       cancer            < 0.5    to the right, improve=1.1459910, (0 missing)
##       reimbursement2008 < 19645  to the right, improve=1.0270110, (0 missing)
##       age               < 80     to the left,  improve=0.9767058, (0 missing)
##       depression        < 0.5    to the right, improve=0.7631860, (0 missing)
## 
## Node number 4065: 8 observations
##   predicted class=B3  expected loss=0.375  P(node) =0.0004
##     class counts:     2     0     5     1     0
##    probabilities: 0.250 0.000 0.625 0.125 0.000 
## 
## Node number 4066: 9 observations
##   predicted class=B1  expected loss=0.6666667  P(node) =0.00045
##     class counts:     3     1     3     2     0
##    probabilities: 0.333 0.111 0.333 0.222 0.000 
## 
## Node number 4067: 19 observations
##   predicted class=B2  expected loss=0.4736842  P(node) =0.00095
##     class counts:     2    10     0     7     0
##    probabilities: 0.105 0.526 0.000 0.368 0.000 
## 
## Node number 4068: 32 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.40625  P(node) =0.0016
##     class counts:     4    19     4     3     2
##    probabilities: 0.125 0.594 0.125 0.094 0.062 
##   left son=8136 (7 obs) right son=8137 (25 obs)
##   Primary splits:
##       reimbursement2008 < 25510  to the right, improve=3.0153570, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.3731060, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9474206, (0 missing)
##       age               < 72.5   to the right, improve=0.6125000, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.4791667, (0 missing)
## 
## Node number 4069: 9 observations
##   predicted class=B1  expected loss=0.6666667  P(node) =0.00045
##     class counts:     3     1     2     1     2
##    probabilities: 0.333 0.111 0.222 0.111 0.222 
## 
## Node number 4070: 81 observations,    complexity param=0.000380286
##   predicted class=B2  expected loss=0.654321  P(node) =0.00405
##     class counts:    14    28    18    18     3
##    probabilities: 0.173 0.346 0.222 0.222 0.037 
##   left son=8140 (35 obs) right son=8141 (46 obs)
##   Primary splits:
##       age               < 73.5   to the left,  improve=1.8360860, (0 missing)
##       reimbursement2008 < 18450  to the right, improve=1.8267530, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.4464610, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.6743146, (0 missing)
##       bucket2008        < 3.5    to the right, improve=0.6083053, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 18450  to the right, agree=0.741, adj=0.400, (0 split)
##       bucket2008        < 3.5    to the right, agree=0.728, adj=0.371, (0 split)
##       osteoporosis      < 0.5    to the right, agree=0.654, adj=0.200, (0 split)
##       cancer            < 0.5    to the right, agree=0.580, adj=0.029, (0 split)
##       depression        < 0.5    to the left,  agree=0.580, adj=0.029, (0 split)
## 
## Node number 4071: 16 observations
##   predicted class=B4  expected loss=0.5  P(node) =0.0008
##     class counts:     0     2     5     8     1
##    probabilities: 0.000 0.125 0.312 0.500 0.062 
## 
## Node number 4072: 36 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5277778  P(node) =0.0018
##     class counts:     4    17    13     0     2
##    probabilities: 0.111 0.472 0.361 0.000 0.056 
##   left son=8144 (29 obs) right son=8145 (7 obs)
##   Primary splits:
##       reimbursement2008 < 22930  to the right, improve=1.4020250, (0 missing)
##       age               < 70.5   to the left,  improve=1.0793650, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.3754730, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3367677, (0 missing)
##       cancer            < 0.5    to the right, improve=0.2222222, (0 missing)
## 
## Node number 4073: 89 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5842697  P(node) =0.00445
##     class counts:    13    37    19    16     4
##    probabilities: 0.146 0.416 0.213 0.180 0.045 
##   left son=8146 (55 obs) right son=8147 (34 obs)
##   Primary splits:
##       reimbursement2008 < 17640  to the right, improve=1.6152980, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.1922490, (0 missing)
##       age               < 83.5   to the left,  improve=1.1121530, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.0048700, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9641839, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.775, adj=0.412, (0 split)
## 
## Node number 4088: 30 observations
##   predicted class=B2  expected loss=0.3333333  P(node) =0.0015
##     class counts:     2    20     2     4     2
##    probabilities: 0.067 0.667 0.067 0.133 0.067 
## 
## Node number 4089: 17 observations
##   predicted class=B3  expected loss=0.5294118  P(node) =0.00085
##     class counts:     1     5     8     2     1
##    probabilities: 0.059 0.294 0.471 0.118 0.059 
## 
## Node number 4090: 11 observations
##   predicted class=B2  expected loss=0.3636364  P(node) =0.00055
##     class counts:     1     7     2     1     0
##    probabilities: 0.091 0.636 0.182 0.091 0.000 
## 
## Node number 4091: 33 observations,    complexity param=0.0002662002
##   predicted class=B4  expected loss=0.5757576  P(node) =0.00165
##     class counts:     2    12     5    14     0
##    probabilities: 0.061 0.364 0.152 0.424 0.000 
##   left son=8182 (17 obs) right son=8183 (16 obs)
##   Primary splits:
##       arthritis         < 0.5    to the right, improve=1.3990640, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.8990642, (0 missing)
##       reimbursement2008 < 28890  to the right, improve=0.8332194, (0 missing)
##       age               < 66.5   to the right, improve=0.6404040, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3459596, (0 missing)
##   Surrogate splits:
##       age               < 60.5   to the right, agree=0.636, adj=0.250, (0 split)
##       cancer            < 0.5    to the right, agree=0.636, adj=0.250, (0 split)
##       reimbursement2008 < 28890  to the right, agree=0.636, adj=0.250, (0 split)
##       copd              < 0.5    to the right, agree=0.576, adj=0.125, (0 split)
##       depression        < 0.5    to the right, agree=0.576, adj=0.125, (0 split)
## 
## Node number 4092: 26 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.6538462  P(node) =0.0013
##     class counts:     6     9     5     5     1
##    probabilities: 0.231 0.346 0.192 0.192 0.038 
##   left son=8184 (13 obs) right son=8185 (13 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=2.4615380, (0 missing)
##       age               < 77.5   to the left,  improve=0.8995726, (0 missing)
##       reimbursement2008 < 45075  to the right, improve=0.8134615, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6061307, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.4615385, (0 missing)
##   Surrogate splits:
##       age               < 72.5   to the left,  agree=0.615, adj=0.231, (0 split)
##       reimbursement2008 < 41035  to the left,  agree=0.615, adj=0.231, (0 split)
##       bucket2008        < 4.5    to the left,  agree=0.577, adj=0.154, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.538, adj=0.077, (0 split)
##       arthritis         < 0.5    to the left,  agree=0.538, adj=0.077, (0 split)
## 
## Node number 4093: 71 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5774648  P(node) =0.00355
##     class counts:     0    30    12    23     6
##    probabilities: 0.000 0.423 0.169 0.324 0.085 
##   left son=8186 (13 obs) right son=8187 (58 obs)
##   Primary splits:
##       reimbursement2008 < 38625  to the left,  improve=1.735906, (0 missing)
##       age               < 79.5   to the left,  improve=1.085709, (0 missing)
##       bucket2008        < 4.5    to the left,  improve=1.083189, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.081118, (0 missing)
##       cancer            < 0.5    to the right, improve=0.997176, (0 missing)
##   Surrogate splits:
##       age < 86.5   to the right, agree=0.831, adj=0.077, (0 split)
## 
## Node number 4094: 180 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.7  P(node) =0.009
##     class counts:    14    54    53    51     8
##    probabilities: 0.078 0.300 0.294 0.283 0.044 
##   left son=8188 (150 obs) right son=8189 (30 obs)
##   Primary splits:
##       age               < 82.5   to the left,  improve=1.8600000, (0 missing)
##       reimbursement2008 < 101155 to the left,  improve=1.3289020, (0 missing)
##       bucket2008        < 4.5    to the right, improve=1.0857140, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.9828717, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.9785714, (0 missing)
## 
## Node number 4095: 54 observations,    complexity param=0.0001521144
##   predicted class=B4  expected loss=0.5185185  P(node) =0.0027
##     class counts:     4    11    10    26     3
##    probabilities: 0.074 0.204 0.185 0.481 0.056 
##   left son=8190 (39 obs) right son=8191 (15 obs)
##   Primary splits:
##       reimbursement2008 < 35865  to the left,  improve=2.7310540, (0 missing)
##       age               < 83.5   to the right, improve=1.5895620, (0 missing)
##       depression        < 0.5    to the right, improve=1.0054170, (0 missing)
##       cancer            < 0.5    to the right, improve=0.8050992, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4588930, (0 missing)
## 
## Node number 5142: 398 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.1758794  P(node) =0.0199
##     class counts:   328    39    26     3     2
##    probabilities: 0.824 0.098 0.065 0.008 0.005 
##   left son=10284 (321 obs) right son=10285 (77 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=0.5824155, (0 missing)
##       age               < 86.5   to the left,  improve=0.5329233, (0 missing)
##       reimbursement2008 < 315    to the left,  improve=0.4958627, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3680496, (0 missing)
##       depression        < 0.5    to the left,  improve=0.2599538, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.809, adj=0.013, (0 split)
## 
## Node number 5143: 32 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.28125  P(node) =0.0016
##     class counts:    23     8     0     1     0
##    probabilities: 0.719 0.250 0.000 0.031 0.000 
##   left son=10286 (10 obs) right son=10287 (22 obs)
##   Primary splits:
##       age               < 83.5   to the right, improve=0.81931820, (0 missing)
##       reimbursement2008 < 485    to the right, improve=0.04142157, (0 missing)
##       ihd               < 0.5    to the right, improve=0.02035714, (0 missing)
## 
## Node number 5766: 51 observations
##   predicted class=B1  expected loss=0.2941176  P(node) =0.00255
##     class counts:    36     6     7     2     0
##    probabilities: 0.706 0.118 0.137 0.039 0.000 
## 
## Node number 5767: 8 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0004
##     class counts:     3     4     1     0     0
##    probabilities: 0.375 0.500 0.125 0.000 0.000 
## 
## Node number 5768: 79 observations
##   predicted class=B1  expected loss=0.2278481  P(node) =0.00395
##     class counts:    61    11     6     1     0
##    probabilities: 0.772 0.139 0.076 0.013 0.000 
## 
## Node number 5769: 30 observations,    complexity param=8.450799e-05
##   predicted class=B1  expected loss=0.4333333  P(node) =0.0015
##     class counts:    17    10     3     0     0
##    probabilities: 0.567 0.333 0.100 0.000 0.000 
##   left son=11538 (23 obs) right son=11539 (7 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=2.1370600, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.8333333, (0 missing)
##       reimbursement2008 < 1465   to the right, improve=0.7869048, (0 missing)
##       age               < 75.5   to the right, improve=0.3803922, (0 missing)
## 
## Node number 5786: 9 observations
##   predicted class=B1  expected loss=0.2222222  P(node) =0.00045
##     class counts:     7     1     0     1     0
##    probabilities: 0.778 0.111 0.000 0.111 0.000 
## 
## Node number 5787: 11 observations
##   predicted class=B2  expected loss=0.5454545  P(node) =0.00055
##     class counts:     4     5     1     1     0
##    probabilities: 0.364 0.455 0.091 0.091 0.000 
## 
## Node number 5790: 11 observations
##   predicted class=B1  expected loss=0.4545455  P(node) =0.00055
##     class counts:     6     5     0     0     0
##    probabilities: 0.545 0.455 0.000 0.000 0.000 
## 
## Node number 5791: 9 observations
##   predicted class=B2  expected loss=0.3333333  P(node) =0.00045
##     class counts:     3     6     0     0     0
##    probabilities: 0.333 0.667 0.000 0.000 0.000 
## 
## Node number 5898: 10 observations
##   predicted class=B1  expected loss=0.1  P(node) =0.0005
##     class counts:     9     0     1     0     0
##    probabilities: 0.900 0.000 0.100 0.000 0.000 
## 
## Node number 5899: 127 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3149606  P(node) =0.00635
##     class counts:    87    25    12     3     0
##    probabilities: 0.685 0.197 0.094 0.024 0.000 
##   left son=11798 (8 obs) right son=11799 (119 obs)
##   Primary splits:
##       reimbursement2008 < 875    to the left,  improve=0.6516410, (0 missing)
##       depression        < 0.5    to the right, improve=0.4432881, (0 missing)
##       age               < 91     to the right, improve=0.4331536, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1827812, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.1471502, (0 missing)
## 
## Node number 5902: 7 observations
##   predicted class=B1  expected loss=0.5714286  P(node) =0.00035
##     class counts:     3     2     2     0     0
##    probabilities: 0.429 0.286 0.286 0.000 0.000 
## 
## Node number 5903: 13 observations
##   predicted class=B2  expected loss=0.5384615  P(node) =0.00065
##     class counts:     4     6     2     1     0
##    probabilities: 0.308 0.462 0.154 0.077 0.000 
## 
## Node number 6054: 10 observations
##   predicted class=B1  expected loss=0.1  P(node) =0.0005
##     class counts:     9     1     0     0     0
##    probabilities: 0.900 0.100 0.000 0.000 0.000 
## 
## Node number 6055: 115 observations,    complexity param=6.084576e-05
##   predicted class=B1  expected loss=0.3652174  P(node) =0.00575
##     class counts:    73    29    12     0     1
##    probabilities: 0.635 0.252 0.104 0.000 0.009 
##   left son=12110 (36 obs) right son=12111 (79 obs)
##   Primary splits:
##       age               < 73.5   to the right, improve=0.9624839, (0 missing)
##       reimbursement2008 < 1075   to the right, improve=0.7285649, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6802899, (0 missing)
##       kidney            < 0.5    to the right, improve=0.6593008, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.2298137, (0 missing)
##   Surrogate splits:
##       stroke < 0.5    to the right, agree=0.704, adj=0.056, (0 split)
## 
## Node number 6094: 18 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.0009
##     class counts:     8    10     0     0     0
##    probabilities: 0.444 0.556 0.000 0.000 0.000 
## 
## Node number 6095: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     0     3     4     0     0
##    probabilities: 0.000 0.429 0.571 0.000 0.000 
## 
## Node number 6154: 59 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3389831  P(node) =0.00295
##     class counts:    39    15     4     0     1
##    probabilities: 0.661 0.254 0.068 0.000 0.017 
##   left son=12308 (15 obs) right son=12309 (44 obs)
##   Primary splits:
##       reimbursement2008 < 2050   to the right, improve=1.2428860, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.4978711, (0 missing)
##       age               < 47     to the right, improve=0.3049186, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1023175, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the right, agree=0.78, adj=0.133, (0 split)
## 
## Node number 6155: 10 observations
##   predicted class=B1  expected loss=0.6  P(node) =0.0005
##     class counts:     4     4     2     0     0
##    probabilities: 0.400 0.400 0.200 0.000 0.000 
## 
## Node number 6168: 49 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3877551  P(node) =0.00245
##     class counts:    30    15     4     0     0
##    probabilities: 0.612 0.306 0.082 0.000 0.000 
##   left son=12336 (11 obs) right son=12337 (38 obs)
##   Primary splits:
##       reimbursement2008 < 2155   to the right, improve=0.9152427, (0 missing)
##       age               < 71.5   to the right, improve=0.6536797, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2980178, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.2857143, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.0252905, (0 missing)
## 
## Node number 6169: 9 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.00045
##     class counts:     4     5     0     0     0
##    probabilities: 0.444 0.556 0.000 0.000 0.000 
## 
## Node number 6174: 13 observations
##   predicted class=B2  expected loss=0.6153846  P(node) =0.00065
##     class counts:     4     5     3     1     0
##    probabilities: 0.308 0.385 0.231 0.077 0.000 
## 
## Node number 6175: 8 observations
##   predicted class=B4  expected loss=0.625  P(node) =0.0004
##     class counts:     2     1     2     3     0
##    probabilities: 0.250 0.125 0.250 0.375 0.000 
## 
## Node number 6224: 23 observations
##   predicted class=B1  expected loss=0.2173913  P(node) =0.00115
##     class counts:    18     5     0     0     0
##    probabilities: 0.783 0.217 0.000 0.000 0.000 
## 
## Node number 6225: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     2     5     0     0     0
##    probabilities: 0.286 0.714 0.000 0.000 0.000 
## 
## Node number 6362: 45 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.4888889  P(node) =0.00225
##     class counts:    23    13     8     0     1
##    probabilities: 0.511 0.289 0.178 0.000 0.022 
##   left son=12724 (32 obs) right son=12725 (13 obs)
##   Primary splits:
##       arthritis         < 0.5    to the left,  improve=1.9146370, (0 missing)
##       age               < 78.5   to the left,  improve=1.5873020, (0 missing)
##       reimbursement2008 < 2165   to the right, improve=1.3407410, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.7235888, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6008354, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2895   to the left,  agree=0.778, adj=0.231, (0 split)
## 
## Node number 6363: 60 observations,    complexity param=0.0002028192
##   predicted class=B2  expected loss=0.6  P(node) =0.003
##     class counts:    21    24    13     2     0
##    probabilities: 0.350 0.400 0.217 0.033 0.000 
##   left son=12726 (36 obs) right son=12727 (24 obs)
##   Primary splits:
##       reimbursement2008 < 2215   to the right, improve=2.1944440, (0 missing)
##       age               < 71.5   to the left,  improve=1.3810440, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7444444, (0 missing)
##       copd              < 0.5    to the right, improve=0.2083333, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.1250000, (0 missing)
##   Surrogate splits:
##       age < 73.5   to the left,  agree=0.633, adj=0.083, (0 split)
## 
## Node number 6670: 42 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.5  P(node) =0.0021
##     class counts:    21    18     2     1     0
##    probabilities: 0.500 0.429 0.048 0.024 0.000 
##   left son=13340 (34 obs) right son=13341 (8 obs)
##   Primary splits:
##       reimbursement2008 < 2305   to the left,  improve=0.8284314, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6695992, (0 missing)
##       age               < 79.5   to the left,  improve=0.5952381, (0 missing)
##       kidney            < 0.5    to the right, improve=0.1919192, (0 missing)
##       copd              < 0.5    to the left,  improve=0.1809524, (0 missing)
## 
## Node number 6671: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     2     5     0     1     0
##    probabilities: 0.250 0.625 0.000 0.125 0.000 
## 
## Node number 6680: 19 observations
##   predicted class=B1  expected loss=0.2631579  P(node) =0.00095
##     class counts:    14     3     2     0     0
##    probabilities: 0.737 0.158 0.105 0.000 0.000 
## 
## Node number 6681: 14 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0007
##     class counts:     5     7     1     0     1
##    probabilities: 0.357 0.500 0.071 0.000 0.071 
## 
## Node number 6682: 12 observations
##   predicted class=B1  expected loss=0.4166667  P(node) =0.0006
##     class counts:     7     5     0     0     0
##    probabilities: 0.583 0.417 0.000 0.000 0.000 
## 
## Node number 6683: 18 observations
##   predicted class=B2  expected loss=0.3333333  P(node) =0.0009
##     class counts:     5    12     1     0     0
##    probabilities: 0.278 0.667 0.056 0.000 0.000 
## 
## Node number 6688: 96 observations
##   predicted class=B1  expected loss=0.3020833  P(node) =0.0048
##     class counts:    67    19     7     3     0
##    probabilities: 0.698 0.198 0.073 0.031 0.000 
## 
## Node number 6689: 115 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.4434783  P(node) =0.00575
##     class counts:    64    32    11     7     1
##    probabilities: 0.557 0.278 0.096 0.061 0.009 
##   left son=13378 (20 obs) right son=13379 (95 obs)
##   Primary splits:
##       age               < 60     to the left,  improve=1.2386730, (0 missing)
##       reimbursement2008 < 1735   to the left,  improve=1.2165300, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5300884, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4281976, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1607321, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1585   to the left,  agree=0.843, adj=0.1, (0 split)
## 
## Node number 6704: 88 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5454545  P(node) =0.0044
##     class counts:    36    40     6     5     1
##    probabilities: 0.409 0.455 0.068 0.057 0.011 
##   left son=13408 (55 obs) right son=13409 (33 obs)
##   Primary splits:
##       reimbursement2008 < 1925   to the left,  improve=0.8106061, (0 missing)
##       age               < 66.5   to the right, improve=0.6676136, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.6409091, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.6351931, (0 missing)
##       cancer            < 0.5    to the right, improve=0.5363636, (0 missing)
##   Surrogate splits:
##       alzheimers < 0.5    to the left,  agree=0.659, adj=0.091, (0 split)
##       age        < 72.5   to the left,  agree=0.648, adj=0.061, (0 split)
## 
## Node number 6705: 10 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0005
##     class counts:     5     2     0     3     0
##    probabilities: 0.500 0.200 0.000 0.300 0.000 
## 
## Node number 6708: 16 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0008
##     class counts:     5     8     3     0     0
##    probabilities: 0.312 0.500 0.188 0.000 0.000 
## 
## Node number 6709: 7 observations
##   predicted class=B1  expected loss=0.5714286  P(node) =0.00035
##     class counts:     3     1     3     0     0
##    probabilities: 0.429 0.143 0.429 0.000 0.000 
## 
## Node number 6850: 10 observations
##   predicted class=B1  expected loss=0.2  P(node) =0.0005
##     class counts:     8     0     1     1     0
##    probabilities: 0.800 0.000 0.100 0.100 0.000 
## 
## Node number 6851: 24 observations,    complexity param=0.000190143
##   predicted class=B1  expected loss=0.5  P(node) =0.0012
##     class counts:    12    10     1     1     0
##    probabilities: 0.500 0.417 0.042 0.042 0.000 
##   left son=13702 (14 obs) right son=13703 (10 obs)
##   Primary splits:
##       reimbursement2008 < 1775   to the left,  improve=2.23571400, (0 missing)
##       age               < 65.5   to the left,  improve=0.80714290, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.25000000, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.08333333, (0 missing)
##   Surrogate splits:
##       age          < 47     to the right, agree=0.667, adj=0.2, (0 split)
##       osteoporosis < 0.5    to the left,  agree=0.667, adj=0.2, (0 split)
## 
## Node number 6858: 22 observations
##   predicted class=B2  expected loss=0.5454545  P(node) =0.0011
##     class counts:     4    10     6     2     0
##    probabilities: 0.182 0.455 0.273 0.091 0.000 
## 
## Node number 6859: 7 observations
##   predicted class=B1  expected loss=0.5714286  P(node) =0.00035
##     class counts:     3     0     3     1     0
##    probabilities: 0.429 0.000 0.429 0.143 0.000 
## 
## Node number 6870: 46 observations,    complexity param=0.000253524
##   predicted class=B1  expected loss=0.5869565  P(node) =0.0023
##     class counts:    19    19     8     0     0
##    probabilities: 0.413 0.413 0.174 0.000 0.000 
##   left son=13740 (7 obs) right son=13741 (39 obs)
##   Primary splits:
##       copd              < 0.5    to the right, improve=2.2610290, (0 missing)
##       heart.failure     < 0.5    to the right, improve=2.1976590, (0 missing)
##       reimbursement2008 < 2225   to the left,  improve=1.5721340, (0 missing)
##       diabetes          < 0.5    to the right, improve=1.1052510, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.7791149, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2110   to the left,  agree=0.87, adj=0.143, (0 split)
## 
## Node number 6871: 53 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4150943  P(node) =0.00265
##     class counts:    13    31     8     1     0
##    probabilities: 0.245 0.585 0.151 0.019 0.000 
##   left son=13742 (13 obs) right son=13743 (40 obs)
##   Primary splits:
##       reimbursement2008 < 1795   to the left,  improve=2.1412920, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.3502660, (0 missing)
##       diabetes          < 0.5    to the left,  improve=1.1700920, (0 missing)
##       age               < 75.5   to the right, improve=0.9132407, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.4028302, (0 missing)
##   Surrogate splits:
##       age  < 81.5   to the right, agree=0.792, adj=0.154, (0 split)
##       copd < 0.5    to the right, agree=0.792, adj=0.154, (0 split)
## 
## Node number 6934: 41 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5609756  P(node) =0.00205
##     class counts:    18    17     6     0     0
##    probabilities: 0.439 0.415 0.146 0.000 0.000 
##   left son=13868 (30 obs) right son=13869 (11 obs)
##   Primary splits:
##       reimbursement2008 < 2680   to the right, improve=1.4919440, (0 missing)
##       age               < 74.5   to the left,  improve=0.6876399, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.4137873, (0 missing)
##       depression        < 0.5    to the left,  improve=0.2054539, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1305018, (0 missing)
## 
## Node number 6935: 14 observations
##   predicted class=B1  expected loss=0.3571429  P(node) =0.0007
##     class counts:     9     0     2     3     0
##    probabilities: 0.643 0.000 0.143 0.214 0.000 
## 
## Node number 6936: 7 observations
##   predicted class=B1  expected loss=0  P(node) =0.00035
##     class counts:     7     0     0     0     0
##    probabilities: 1.000 0.000 0.000 0.000 0.000 
## 
## Node number 6937: 51 observations,    complexity param=0.0001014096
##   predicted class=B1  expected loss=0.4901961  P(node) =0.00255
##     class counts:    26    11    10     2     2
##    probabilities: 0.510 0.216 0.196 0.039 0.039 
##   left son=13874 (24 obs) right son=13875 (27 obs)
##   Primary splits:
##       reimbursement2008 < 2865   to the left,  improve=1.0511980, (0 missing)
##       age               < 70.5   to the right, improve=0.8104575, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.4304506, (0 missing)
##       kidney            < 0.5    to the right, improve=0.2867201, (0 missing)
##       depression        < 0.5    to the right, improve=0.2437908, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.902, adj=0.792, (0 split)
##       age        < 71.5   to the left,  agree=0.627, adj=0.208, (0 split)
##       kidney     < 0.5    to the right, agree=0.627, adj=0.208, (0 split)
##       copd       < 0.5    to the left,  agree=0.569, adj=0.083, (0 split)
##       depression < 0.5    to the right, agree=0.549, adj=0.042, (0 split)
## 
## Node number 6938: 33 observations,    complexity param=0.0002662002
##   predicted class=B2  expected loss=0.5454545  P(node) =0.00165
##     class counts:    13    15     4     1     0
##    probabilities: 0.394 0.455 0.121 0.030 0.000 
##   left son=13876 (7 obs) right son=13877 (26 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=0.8421578, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7121212, (0 missing)
##       reimbursement2008 < 2665   to the left,  improve=0.5454545, (0 missing)
##       age               < 82.5   to the left,  improve=0.5454545, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.3787879, (0 missing)
## 
## Node number 6939: 13 observations
##   predicted class=B3  expected loss=0.6153846  P(node) =0.00065
##     class counts:     4     3     5     1     0
##    probabilities: 0.308 0.231 0.385 0.077 0.000 
## 
## Node number 6980: 23 observations
##   predicted class=B1  expected loss=0.3478261  P(node) =0.00115
##     class counts:    15     2     3     3     0
##    probabilities: 0.652 0.087 0.130 0.130 0.000 
## 
## Node number 6981: 44 observations,    complexity param=0.000253524
##   predicted class=B1  expected loss=0.5227273  P(node) =0.0022
##     class counts:    21    16     3     4     0
##    probabilities: 0.477 0.364 0.068 0.091 0.000 
##   left son=13962 (23 obs) right son=13963 (21 obs)
##   Primary splits:
##       reimbursement2008 < 2715   to the left,  improve=0.8579898, (0 missing)
##       depression        < 0.5    to the right, improve=0.8196673, (0 missing)
##       age               < 66.5   to the right, improve=0.5631313, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3181818, (0 missing)
##       copd              < 0.5    to the right, improve=0.1969697, (0 missing)
##   Surrogate splits:
##       age        < 66.5   to the right, agree=0.614, adj=0.190, (0 split)
##       depression < 0.5    to the right, agree=0.545, adj=0.048, (0 split)
## 
## Node number 6982: 13 observations
##   predicted class=B1  expected loss=0.3846154  P(node) =0.00065
##     class counts:     8     4     1     0     0
##    probabilities: 0.615 0.308 0.077 0.000 0.000 
## 
## Node number 6983: 45 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.4444444  P(node) =0.00225
##     class counts:    12    25     4     4     0
##    probabilities: 0.267 0.556 0.089 0.089 0.000 
##   left son=13966 (10 obs) right son=13967 (35 obs)
##   Primary splits:
##       reimbursement2008 < 3285   to the right, improve=1.5428570, (0 missing)
##       depression        < 0.5    to the left,  improve=1.2040490, (0 missing)
##       age               < 71     to the right, improve=1.0175680, (0 missing)
##       copd              < 0.5    to the left,  improve=0.9777778, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.3105769, (0 missing)
## 
## Node number 7004: 19 observations
##   predicted class=B2  expected loss=0.5263158  P(node) =0.00095
##     class counts:     4     9     4     2     0
##    probabilities: 0.211 0.474 0.211 0.105 0.000 
## 
## Node number 7005: 20 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.6  P(node) =0.001
##     class counts:     8     3     5     4     0
##    probabilities: 0.400 0.150 0.250 0.200 0.000 
##   left son=14010 (8 obs) right son=14011 (12 obs)
##   Primary splits:
##       reimbursement2008 < 2955   to the left,  improve=1.5500000, (0 missing)
##       bucket2008        < 1.5    to the left,  improve=0.7166667, (0 missing)
##       age               < 79     to the left,  improve=0.4010101, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.80, adj=0.500, (0 split)
##       age        < 58.5   to the left,  agree=0.70, adj=0.250, (0 split)
##       cancer     < 0.5    to the right, agree=0.65, adj=0.125, (0 split)
## 
## Node number 7040: 32 observations,    complexity param=0.0002788764
##   predicted class=B1  expected loss=0.46875  P(node) =0.0016
##     class counts:    17    11     4     0     0
##    probabilities: 0.531 0.344 0.125 0.000 0.000 
##   left son=14080 (18 obs) right son=14081 (14 obs)
##   Primary splits:
##       depression   < 0.5    to the left,  improve=1.3700400, (0 missing)
##       copd         < 0.5    to the left,  improve=1.1875000, (0 missing)
##       diabetes     < 0.5    to the right, improve=0.7541667, (0 missing)
##       osteoporosis < 0.5    to the left,  improve=0.4875000, (0 missing)
##       age          < 68.5   to the left,  improve=0.4494048, (0 missing)
##   Surrogate splits:
##       copd              < 0.5    to the left,  agree=0.688, adj=0.286, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.688, adj=0.286, (0 split)
##       age               < 37.5   to the right, agree=0.625, adj=0.143, (0 split)
##       reimbursement2008 < 2915   to the left,  agree=0.625, adj=0.143, (0 split)
## 
## Node number 7041: 8 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0004
##     class counts:     1     4     1     1     1
##    probabilities: 0.125 0.500 0.125 0.125 0.125 
## 
## Node number 7042: 52 observations
##   predicted class=B2  expected loss=0.4423077  P(node) =0.0026
##     class counts:    15    29     7     1     0
##    probabilities: 0.288 0.558 0.135 0.019 0.000 
## 
## Node number 7043: 12 observations
##   predicted class=B1  expected loss=0.5833333  P(node) =0.0006
##     class counts:     5     3     2     2     0
##    probabilities: 0.417 0.250 0.167 0.167 0.000 
## 
## Node number 7046: 19 observations
##   predicted class=B2  expected loss=0.6315789  P(node) =0.00095
##     class counts:     6     7     6     0     0
##    probabilities: 0.316 0.368 0.316 0.000 0.000 
## 
## Node number 7047: 7 observations
##   predicted class=B3  expected loss=0.1428571  P(node) =0.00035
##     class counts:     1     0     6     0     0
##    probabilities: 0.143 0.000 0.857 0.000 0.000 
## 
## Node number 7194: 79 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4177215  P(node) =0.00395
##     class counts:    46    17    15     1     0
##    probabilities: 0.582 0.215 0.190 0.013 0.000 
##   left son=14388 (32 obs) right son=14389 (47 obs)
##   Primary splits:
##       reimbursement2008 < 4235   to the left,  improve=1.8012560, (0 missing)
##       age               < 70.5   to the right, improve=1.0692790, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.6128692, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4137464, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.3172132, (0 missing)
##   Surrogate splits:
##       age < 76.5   to the right, agree=0.646, adj=0.125, (0 split)
## 
## Node number 7195: 18 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0009
##     class counts:     6     9     2     1     0
##    probabilities: 0.333 0.500 0.111 0.056 0.000 
## 
## Node number 7502: 10 observations
##   predicted class=B1  expected loss=0.6  P(node) =0.0005
##     class counts:     4     3     2     1     0
##    probabilities: 0.400 0.300 0.200 0.100 0.000 
## 
## Node number 7503: 15 observations
##   predicted class=B2  expected loss=0.3333333  P(node) =0.00075
##     class counts:     2    10     2     1     0
##    probabilities: 0.133 0.667 0.133 0.067 0.000 
## 
## Node number 7516: 18 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.0009
##     class counts:     4    10     3     1     0
##    probabilities: 0.222 0.556 0.167 0.056 0.000 
## 
## Node number 7517: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     1     2     3     1     0
##    probabilities: 0.143 0.286 0.429 0.143 0.000 
## 
## Node number 7682: 7 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.00035
##     class counts:     4     3     0     0     0
##    probabilities: 0.571 0.429 0.000 0.000 0.000 
## 
## Node number 7683: 17 observations
##   predicted class=B2  expected loss=0.4117647  P(node) =0.00085
##     class counts:     6    10     1     0     0
##    probabilities: 0.353 0.588 0.059 0.000 0.000 
## 
## Node number 7686: 76 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4868421  P(node) =0.0038
##     class counts:    39    17    18     2     0
##    probabilities: 0.513 0.224 0.237 0.026 0.000 
##   left son=15372 (20 obs) right son=15373 (56 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the right, improve=1.6184210, (0 missing)
##       reimbursement2008 < 3755   to the left,  improve=1.0173570, (0 missing)
##       age               < 45.5   to the left,  improve=0.4522720, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4366029, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.4050802, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 3515   to the left,  agree=0.763, adj=0.1, (0 split)
## 
## Node number 7687: 28 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0014
##     class counts:     8    14     5     1     0
##    probabilities: 0.286 0.500 0.179 0.036 0.000 
## 
## Node number 7698: 9 observations
##   predicted class=B1  expected loss=0.5555556  P(node) =0.00045
##     class counts:     4     2     0     2     1
##    probabilities: 0.444 0.222 0.000 0.222 0.111 
## 
## Node number 7699: 15 observations
##   predicted class=B2  expected loss=0.4666667  P(node) =0.00075
##     class counts:     2     8     2     3     0
##    probabilities: 0.133 0.533 0.133 0.200 0.000 
## 
## Node number 7712: 11 observations
##   predicted class=B1  expected loss=0.2727273  P(node) =0.00055
##     class counts:     8     0     2     1     0
##    probabilities: 0.727 0.000 0.182 0.091 0.000 
## 
## Node number 7713: 106 observations,    complexity param=0.0003295812
##   predicted class=B1  expected loss=0.5  P(node) =0.0053
##     class counts:    53    35    11     7     0
##    probabilities: 0.500 0.330 0.104 0.066 0.000 
##   left son=15426 (85 obs) right son=15427 (21 obs)
##   Primary splits:
##       reimbursement2008 < 6040   to the right, improve=2.0740760, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.1004920, (0 missing)
##       age               < 83.5   to the left,  improve=0.9104868, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4595413, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.4547943, (0 missing)
## 
## Node number 7714: 13 observations
##   predicted class=B1  expected loss=0.4615385  P(node) =0.00065
##     class counts:     7     5     1     0     0
##    probabilities: 0.538 0.385 0.077 0.000 0.000 
## 
## Node number 7715: 14 observations
##   predicted class=B2  expected loss=0.3571429  P(node) =0.0007
##     class counts:     3     9     1     1     0
##    probabilities: 0.214 0.643 0.071 0.071 0.000 
## 
## Node number 7724: 14 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0007
##     class counts:     7     4     3     0     0
##    probabilities: 0.500 0.286 0.214 0.000 0.000 
## 
## Node number 7725: 47 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.3404255  P(node) =0.00235
##     class counts:     7    31     7     2     0
##    probabilities: 0.149 0.660 0.149 0.043 0.000 
##   left son=15450 (26 obs) right son=15451 (21 obs)
##   Primary splits:
##       age               < 81.5   to the left,  improve=1.7492790, (0 missing)
##       copd              < 0.5    to the left,  improve=1.4122830, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.0571870, (0 missing)
##       reimbursement2008 < 6790   to the right, improve=0.9666891, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.4557060, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 6495   to the right, agree=0.596, adj=0.095, (0 split)
##       copd              < 0.5    to the left,  agree=0.574, adj=0.048, (0 split)
## 
## Node number 7726: 49 observations,    complexity param=0.0004056384
##   predicted class=B2  expected loss=0.6122449  P(node) =0.00245
##     class counts:    15    19     7     7     1
##    probabilities: 0.306 0.388 0.143 0.143 0.020 
##   left son=15452 (38 obs) right son=15453 (11 obs)
##   Primary splits:
##       stroke            < 0.5    to the left,  improve=1.7955280, (0 missing)
##       copd              < 0.5    to the left,  improve=1.3997190, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.3583390, (0 missing)
##       reimbursement2008 < 32725  to the left,  improve=1.0680270, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6528868, (0 missing)
## 
## Node number 7727: 19 observations
##   predicted class=B3  expected loss=0.5263158  P(node) =0.00095
##     class counts:     5     4     9     1     0
##    probabilities: 0.263 0.211 0.474 0.053 0.000 
## 
## Node number 7740: 17 observations
##   predicted class=B1  expected loss=0.4705882  P(node) =0.00085
##     class counts:     9     5     2     1     0
##    probabilities: 0.529 0.294 0.118 0.059 0.000 
## 
## Node number 7741: 20 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.55  P(node) =0.001
##     class counts:     5     9     4     2     0
##    probabilities: 0.250 0.450 0.200 0.100 0.000 
##   left son=15482 (7 obs) right son=15483 (13 obs)
##   Primary splits:
##       age               < 86.5   to the right, improve=0.9747253, (0 missing)
##       reimbursement2008 < 4655   to the right, improve=0.9000000, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8208791, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.3666667, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2274725, (0 missing)
##   Surrogate splits:
##       osteoporosis      < 0.5    to the right, agree=0.8, adj=0.429, (0 split)
##       stroke            < 0.5    to the right, agree=0.7, adj=0.143, (0 split)
##       reimbursement2008 < 4145   to the left,  agree=0.7, adj=0.143, (0 split)
## 
## Node number 7786: 11 observations
##   predicted class=B1  expected loss=0.4545455  P(node) =0.00055
##     class counts:     6     2     3     0     0
##    probabilities: 0.545 0.182 0.273 0.000 0.000 
## 
## Node number 7787: 22 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.5  P(node) =0.0011
##     class counts:     2     7    11     2     0
##    probabilities: 0.091 0.318 0.500 0.091 0.000 
##   left son=15574 (8 obs) right son=15575 (14 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=1.23051900, (0 missing)
##       age               < 67.5   to the left,  improve=1.14242400, (0 missing)
##       reimbursement2008 < 9135   to the left,  improve=0.44242420, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.29004330, (0 missing)
##       depression        < 0.5    to the left,  improve=0.08766234, (0 missing)
##   Surrogate splits:
##       age               < 70.5   to the right, agree=0.727, adj=0.25, (0 split)
##       reimbursement2008 < 6475   to the left,  agree=0.727, adj=0.25, (0 split)
## 
## Node number 7788: 26 observations,    complexity param=7.60572e-05
##   predicted class=B2  expected loss=0.6538462  P(node) =0.0013
##     class counts:     6     9     9     2     0
##    probabilities: 0.231 0.346 0.346 0.077 0.000 
##   left son=15576 (16 obs) right son=15577 (10 obs)
##   Primary splits:
##       age               < 76.5   to the right, improve=0.60576920, (0 missing)
##       reimbursement2008 < 5835   to the left,  improve=0.21769730, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.07692308, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.06107226, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4000   to the right, agree=0.654, adj=0.1, (0 split)
## 
## Node number 7789: 7 observations
##   predicted class=B3  expected loss=0.2857143  P(node) =0.00035
##     class counts:     1     0     5     1     0
##    probabilities: 0.143 0.000 0.714 0.143 0.000 
## 
## Node number 7790: 13 observations
##   predicted class=B2  expected loss=0.1538462  P(node) =0.00065
##     class counts:     0    11     1     1     0
##    probabilities: 0.000 0.846 0.077 0.077 0.000 
## 
## Node number 7791: 17 observations
##   predicted class=B3  expected loss=0.5882353  P(node) =0.00085
##     class counts:     1     6     7     3     0
##    probabilities: 0.059 0.353 0.412 0.176 0.000 
## 
## Node number 7880: 7 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.00035
##     class counts:     5     1     1     0     0
##    probabilities: 0.714 0.143 0.143 0.000 0.000 
## 
## Node number 7881: 52 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.4423077  P(node) =0.0026
##     class counts:    14    29     5     3     1
##    probabilities: 0.269 0.558 0.096 0.058 0.019 
##   left son=15762 (32 obs) right son=15763 (20 obs)
##   Primary splits:
##       reimbursement2008 < 4955   to the right, improve=2.1471150, (0 missing)
##       age               < 74.5   to the right, improve=1.8974360, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.3934850, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7370875, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6891199, (0 missing)
##   Surrogate splits:
##       age < 76.5   to the left,  agree=0.75, adj=0.35, (0 split)
## 
## Node number 7882: 18 observations
##   predicted class=B1  expected loss=0.5555556  P(node) =0.0009
##     class counts:     8     5     3     2     0
##    probabilities: 0.444 0.278 0.167 0.111 0.000 
## 
## Node number 7883: 8 observations
##   predicted class=B2  expected loss=0.625  P(node) =0.0004
##     class counts:     0     3     2     3     0
##    probabilities: 0.000 0.375 0.250 0.375 0.000 
## 
## Node number 7902: 15 observations
##   predicted class=B2  expected loss=0.5333333  P(node) =0.00075
##     class counts:     3     7     5     0     0
##    probabilities: 0.200 0.467 0.333 0.000 0.000 
## 
## Node number 7903: 7 observations
##   predicted class=B3  expected loss=0.1428571  P(node) =0.00035
##     class counts:     0     1     6     0     0
##    probabilities: 0.000 0.143 0.857 0.000 0.000 
## 
## Node number 7912: 30 observations
##   predicted class=B2  expected loss=0.2666667  P(node) =0.0015
##     class counts:     3    22     2     3     0
##    probabilities: 0.100 0.733 0.067 0.100 0.000 
## 
## Node number 7913: 22 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.6363636  P(node) =0.0011
##     class counts:     5     8     8     1     0
##    probabilities: 0.227 0.364 0.364 0.045 0.000 
##   left son=15826 (12 obs) right son=15827 (10 obs)
##   Primary splits:
##       age               < 72.5   to the right, improve=1.7666670, (0 missing)
##       reimbursement2008 < 35585  to the left,  improve=1.1142860, (0 missing)
##       copd              < 0.5    to the right, improve=0.2500000, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.1452991, (0 missing)
##       cancer            < 0.5    to the right, improve=0.1452991, (0 missing)
##   Surrogate splits:
##       copd              < 0.5    to the right, agree=0.636, adj=0.2, (0 split)
##       stroke            < 0.5    to the left,  agree=0.636, adj=0.2, (0 split)
##       reimbursement2008 < 28350  to the left,  agree=0.636, adj=0.2, (0 split)
##       cancer            < 0.5    to the right, agree=0.591, adj=0.1, (0 split)
## 
## Node number 7914: 90 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5222222  P(node) =0.0045
##     class counts:    18    43    20     8     1
##    probabilities: 0.200 0.478 0.222 0.089 0.011 
##   left son=15828 (53 obs) right son=15829 (37 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=1.6669610, (0 missing)
##       reimbursement2008 < 7520   to the left,  improve=1.6335890, (0 missing)
##       age               < 72.5   to the right, improve=1.6301840, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=1.1552350, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.9296296, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 6155   to the left,  agree=0.644, adj=0.135, (0 split)
##       age               < 70.5   to the right, agree=0.633, adj=0.108, (0 split)
##       bucket2008        < 2.5    to the left,  agree=0.611, adj=0.054, (0 split)
##       copd              < 0.5    to the left,  agree=0.600, adj=0.027, (0 split)
## 
## Node number 7915: 74 observations,    complexity param=0.0002281716
##   predicted class=B3  expected loss=0.6486486  P(node) =0.0037
##     class counts:    16    25    26     6     1
##    probabilities: 0.216 0.338 0.351 0.081 0.014 
##   left son=15830 (46 obs) right son=15831 (28 obs)
##   Primary splits:
##       age               < 79.5   to the left,  improve=1.5743660, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.1621620, (0 missing)
##       reimbursement2008 < 10440  to the left,  improve=0.7888245, (0 missing)
##       copd              < 0.5    to the left,  improve=0.7705706, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.6708416, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4315   to the right, agree=0.662, adj=0.107, (0 split)
## 
## Node number 7938: 24 observations,    complexity param=0.0002028192
##   predicted class=B3  expected loss=0.625  P(node) =0.0012
##     class counts:     7     8     9     0     0
##    probabilities: 0.292 0.333 0.375 0.000 0.000 
##   left son=15876 (13 obs) right son=15877 (11 obs)
##   Primary splits:
##       reimbursement2008 < 13055  to the right, improve=1.2453380, (0 missing)
##       copd              < 0.5    to the right, improve=0.7166667, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5833333, (0 missing)
##       age               < 90.5   to the right, improve=0.2864146, (0 missing)
##       stroke            < 0.5    to the right, improve=0.2864146, (0 missing)
##   Surrogate splits:
##       copd          < 0.5    to the right, agree=0.667, adj=0.273, (0 split)
##       age           < 93.5   to the left,  agree=0.625, adj=0.182, (0 split)
##       depression    < 0.5    to the left,  agree=0.625, adj=0.182, (0 split)
##       heart.failure < 0.5    to the right, agree=0.583, adj=0.091, (0 split)
##       stroke        < 0.5    to the right, agree=0.583, adj=0.091, (0 split)
## 
## Node number 7939: 8 observations
##   predicted class=B1  expected loss=0.625  P(node) =0.0004
##     class counts:     3     1     0     2     2
##    probabilities: 0.375 0.125 0.000 0.250 0.250 
## 
## Node number 7948: 169 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.591716  P(node) =0.00845
##     class counts:    43    69    21    31     5
##    probabilities: 0.254 0.408 0.124 0.183 0.030 
##   left son=15896 (24 obs) right son=15897 (145 obs)
##   Primary splits:
##       age               < 75.5   to the right, improve=2.0759710, (0 missing)
##       stroke            < 0.5    to the right, improve=1.4276950, (0 missing)
##       reimbursement2008 < 10940  to the left,  improve=0.9442655, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7626810, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4382567, (0 missing)
## 
## Node number 7949: 8 observations
##   predicted class=B3  expected loss=0.5  P(node) =0.0004
##     class counts:     3     0     4     1     0
##    probabilities: 0.375 0.000 0.500 0.125 0.000 
## 
## Node number 7950: 34 observations,    complexity param=0.0004563432
##   predicted class=B3  expected loss=0.6764706  P(node) =0.0017
##     class counts:     9     8    11     4     2
##    probabilities: 0.265 0.235 0.324 0.118 0.059 
##   left son=15900 (10 obs) right son=15901 (24 obs)
##   Primary splits:
##       copd              < 0.5    to the right, improve=1.4882350, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.2805430, (0 missing)
##       reimbursement2008 < 7950   to the right, improve=0.9321506, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.9321506, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5215686, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 13335  to the right, agree=0.765, adj=0.2, (0 split)
## 
## Node number 7951: 57 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.5789474  P(node) =0.00285
##     class counts:     5    24    13    14     1
##    probabilities: 0.088 0.421 0.228 0.246 0.018 
##   left son=15902 (38 obs) right son=15903 (19 obs)
##   Primary splits:
##       reimbursement2008 < 9695   to the right, improve=2.9298250, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.2396330, (0 missing)
##       depression        < 0.5    to the right, improve=1.0943470, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.9573099, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.9534551, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.807, adj=0.421, (0 split)
##       age        < 78.5   to the right, agree=0.702, adj=0.105, (0 split)
## 
## Node number 7960: 48 observations,    complexity param=0.0003650745
##   predicted class=B2  expected loss=0.4791667  P(node) =0.0024
##     class counts:     9    25     7     6     1
##    probabilities: 0.188 0.521 0.146 0.125 0.021 
##   left son=15920 (25 obs) right son=15921 (23 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=1.7330430, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.2714290, (0 missing)
##       age               < 82.5   to the left,  improve=0.9889435, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8949580, (0 missing)
##       reimbursement2008 < 5780   to the right, improve=0.7500000, (0 missing)
##   Surrogate splits:
##       age               < 82.5   to the right, agree=0.625, adj=0.217, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.604, adj=0.174, (0 split)
##       reimbursement2008 < 4785   to the right, agree=0.604, adj=0.174, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.562, adj=0.087, (0 split)
##       ihd               < 0.5    to the left,  agree=0.562, adj=0.087, (0 split)
## 
## Node number 7961: 162 observations,    complexity param=0.0003650745
##   predicted class=B2  expected loss=0.6419753  P(node) =0.0081
##     class counts:    35    58    40    25     4
##    probabilities: 0.216 0.358 0.247 0.154 0.025 
##   left son=15922 (94 obs) right son=15923 (68 obs)
##   Primary splits:
##       reimbursement2008 < 4895   to the left,  improve=2.1304950, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.6052440, (0 missing)
##       ihd               < 0.5    to the right, improve=1.1317140, (0 missing)
##       age               < 59.5   to the left,  improve=0.9109347, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.8391381, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.623, adj=0.103, (0 split)
##       copd   < 0.5    to the left,  agree=0.599, adj=0.044, (0 split)
##       stroke < 0.5    to the left,  agree=0.586, adj=0.015, (0 split)
## 
## Node number 7962: 17 observations
##   predicted class=B2  expected loss=0.4705882  P(node) =0.00085
##     class counts:     0     9     7     0     1
##    probabilities: 0.000 0.529 0.412 0.000 0.059 
## 
## Node number 7963: 8 observations
##   predicted class=B3  expected loss=0.375  P(node) =0.0004
##     class counts:     1     1     5     1     0
##    probabilities: 0.125 0.125 0.625 0.125 0.000 
## 
## Node number 8018: 29 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.5172414  P(node) =0.00145
##     class counts:    10    14     3     2     0
##    probabilities: 0.345 0.483 0.103 0.069 0.000 
##   left son=16036 (22 obs) right son=16037 (7 obs)
##   Primary splits:
##       reimbursement2008 < 4270   to the left,  improve=1.4746980, (0 missing)
##       age               < 64.5   to the right, improve=0.8383341, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6291413, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4761407, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.3805419, (0 missing)
## 
## Node number 8019: 40 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.45  P(node) =0.002
##     class counts:     4    22    10     3     1
##    probabilities: 0.100 0.550 0.250 0.075 0.025 
##   left son=16038 (31 obs) right son=16039 (9 obs)
##   Primary splits:
##       reimbursement2008 < 3995   to the right, improve=2.3557350, (0 missing)
##       age               < 81.5   to the right, improve=0.8598901, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6281362, (0 missing)
##       depression        < 0.5    to the right, improve=0.4033333, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.2700000, (0 missing)
## 
## Node number 8052: 35 observations
##   predicted class=B2  expected loss=0.6  P(node) =0.00175
##     class counts:     7    14     7     6     1
##    probabilities: 0.200 0.400 0.200 0.171 0.029 
## 
## Node number 8053: 152 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5197368  P(node) =0.0076
##     class counts:    13    73    46    16     4
##    probabilities: 0.086 0.480 0.303 0.105 0.026 
##   left son=16106 (130 obs) right son=16107 (22 obs)
##   Primary splits:
##       reimbursement2008 < 13595  to the left,  improve=1.2442950, (0 missing)
##       age               < 95.5   to the right, improve=0.7711988, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.6892208, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.3316563, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.2600877, (0 missing)
## 
## Node number 8128: 10 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0005
##     class counts:     4     5     1     0     0
##    probabilities: 0.400 0.500 0.100 0.000 0.000 
## 
## Node number 8129: 49 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.6734694  P(node) =0.00245
##     class counts:    16     7    11    15     0
##    probabilities: 0.327 0.143 0.224 0.306 0.000 
##   left son=16258 (41 obs) right son=16259 (8 obs)
##   Primary splits:
##       age               < 86.5   to the left,  improve=1.5618470, (0 missing)
##       depression        < 0.5    to the right, improve=1.5156330, (0 missing)
##       cancer            < 0.5    to the right, improve=1.3809520, (0 missing)
##       reimbursement2008 < 19645  to the right, improve=0.8857143, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.6959034, (0 missing)
## 
## Node number 8136: 7 observations
##   predicted class=B1  expected loss=0.5714286  P(node) =0.00035
##     class counts:     3     1     1     2     0
##    probabilities: 0.429 0.143 0.143 0.286 0.000 
## 
## Node number 8137: 25 observations
##   predicted class=B2  expected loss=0.28  P(node) =0.00125
##     class counts:     1    18     3     1     2
##    probabilities: 0.040 0.720 0.120 0.040 0.080 
## 
## Node number 8140: 35 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5142857  P(node) =0.00175
##     class counts:     5    17     6     5     2
##    probabilities: 0.143 0.486 0.171 0.143 0.057 
##   left son=16280 (28 obs) right son=16281 (7 obs)
##   Primary splits:
##       age               < 60     to the right, improve=2.0285710, (0 missing)
##       reimbursement2008 < 20455  to the left,  improve=1.0914290, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9064713, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5840160, (0 missing)
##       stroke            < 0.5    to the right, improve=0.5047619, (0 missing)
## 
## Node number 8141: 46 observations,    complexity param=0.000380286
##   predicted class=B4  expected loss=0.7173913  P(node) =0.0023
##     class counts:     9    11    12    13     1
##    probabilities: 0.196 0.239 0.261 0.283 0.022 
##   left son=16282 (39 obs) right son=16283 (7 obs)
##   Primary splits:
##       age               < 75.5   to the right, improve=1.7130120, (0 missing)
##       reimbursement2008 < 17795  to the right, improve=1.6235180, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.6115561, (0 missing)
##       bucket2008        < 3.5    to the right, improve=0.3603865, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.2409420, (0 missing)
## 
## Node number 8144: 29 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4482759  P(node) =0.00145
##     class counts:     3    16     9     0     1
##    probabilities: 0.103 0.552 0.310 0.000 0.034 
##   left son=16288 (22 obs) right son=16289 (7 obs)
##   Primary splits:
##       age               < 86     to the left,  improve=0.9046126, (0 missing)
##       reimbursement2008 < 24075  to the left,  improve=0.8900383, (0 missing)
##       cancer            < 0.5    to the right, improve=0.6344828, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.5056366, (0 missing)
##       depression        < 0.5    to the right, improve=0.4789272, (0 missing)
## 
## Node number 8145: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     1     1     4     0     1
##    probabilities: 0.143 0.143 0.571 0.000 0.143 
## 
## Node number 8146: 55 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.6  P(node) =0.00275
##     class counts:    13    22     9     9     2
##    probabilities: 0.236 0.400 0.164 0.164 0.036 
##   left son=16292 (20 obs) right son=16293 (35 obs)
##   Primary splits:
##       reimbursement2008 < 18970  to the left,  improve=2.780519, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=2.780519, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.478839, (0 missing)
##       depression        < 0.5    to the left,  improve=1.215758, (0 missing)
##       age               < 83.5   to the right, improve=1.152951, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the left,  agree=1.000, adj=1.00, (0 split)
##       age        < 87     to the right, agree=0.655, adj=0.05, (0 split)
## 
## Node number 8147: 34 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5588235  P(node) =0.0017
##     class counts:     0    15    10     7     2
##    probabilities: 0.000 0.441 0.294 0.206 0.059 
##   left son=16294 (9 obs) right son=16295 (25 obs)
##   Primary splits:
##       age               < 77     to the left,  improve=2.0112420, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.1167850, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.0156860, (0 missing)
##       reimbursement2008 < 16720  to the right, improve=0.6577915, (0 missing)
##       depression        < 0.5    to the left,  improve=0.1471751, (0 missing)
## 
## Node number 8182: 17 observations
##   predicted class=B2  expected loss=0.4705882  P(node) =0.00085
##     class counts:     0     9     1     7     0
##    probabilities: 0.000 0.529 0.059 0.412 0.000 
## 
## Node number 8183: 16 observations
##   predicted class=B4  expected loss=0.5625  P(node) =0.0008
##     class counts:     2     3     4     7     0
##    probabilities: 0.125 0.188 0.250 0.438 0.000 
## 
## Node number 8184: 13 observations
##   predicted class=B1  expected loss=0.5384615  P(node) =0.00065
##     class counts:     6     2     2     2     1
##    probabilities: 0.462 0.154 0.154 0.154 0.077 
## 
## Node number 8185: 13 observations
##   predicted class=B2  expected loss=0.4615385  P(node) =0.00065
##     class counts:     0     7     3     3     0
##    probabilities: 0.000 0.538 0.231 0.231 0.000 
## 
## Node number 8186: 13 observations
##   predicted class=B2  expected loss=0.5384615  P(node) =0.00065
##     class counts:     0     6     5     1     1
##    probabilities: 0.000 0.462 0.385 0.077 0.077 
## 
## Node number 8187: 58 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5862069  P(node) =0.0029
##     class counts:     0    24     7    22     5
##    probabilities: 0.000 0.414 0.121 0.379 0.086 
##   left son=16374 (39 obs) right son=16375 (19 obs)
##   Primary splits:
##       age               < 79.5   to the left,  improve=2.1351850, (0 missing)
##       cancer            < 0.5    to the right, improve=1.3166520, (0 missing)
##       reimbursement2008 < 72235  to the left,  improve=1.1115240, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.7016920, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6656672, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 83625  to the left,  agree=0.724, adj=0.158, (0 split)
##       cancer            < 0.5    to the left,  agree=0.690, adj=0.053, (0 split)
## 
## Node number 8188: 150 observations,    complexity param=0.000507048
##   predicted class=B2  expected loss=0.6733333  P(node) =0.0075
##     class counts:    14    49    42    38     7
##    probabilities: 0.093 0.327 0.280 0.253 0.047 
##   left son=16376 (139 obs) right son=16377 (11 obs)
##   Primary splits:
##       reimbursement2008 < 88685  to the left,  improve=1.8771920, (0 missing)
##       age               < 57.5   to the right, improve=1.3581570, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.0064300, (0 missing)
##       bucket2008        < 4.5    to the right, improve=0.9466667, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8913369, (0 missing)
## 
## Node number 8189: 30 observations,    complexity param=0.0003042288
##   predicted class=B4  expected loss=0.5666667  P(node) =0.0015
##     class counts:     0     5    11    13     1
##    probabilities: 0.000 0.167 0.367 0.433 0.033 
##   left son=16378 (9 obs) right son=16379 (21 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=0.7682540, (0 missing)
##       reimbursement2008 < 58390  to the right, improve=0.5971014, (0 missing)
##       depression        < 0.5    to the right, improve=0.5777778, (0 missing)
##       age               < 85.5   to the left,  improve=0.3948963, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2492754, (0 missing)
##   Surrogate splits:
##       age < 87.5   to the right, agree=0.733, adj=0.111, (0 split)
## 
## Node number 8190: 39 observations,    complexity param=0.0001521144
##   predicted class=B4  expected loss=0.6410256  P(node) =0.00195
##     class counts:     4    10     8    14     3
##    probabilities: 0.103 0.256 0.205 0.359 0.077 
##   left son=16380 (27 obs) right son=16381 (12 obs)
##   Primary splits:
##       depression   < 0.5    to the right, improve=1.4245010, (0 missing)
##       age          < 71.5   to the right, improve=1.2051280, (0 missing)
##       osteoporosis < 0.5    to the left,  improve=1.0439950, (0 missing)
##       copd         < 0.5    to the left,  improve=0.8689459, (0 missing)
##       cancer       < 0.5    to the left,  improve=0.6652422, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 35330  to the left,  agree=0.744, adj=0.167, (0 split)
## 
## Node number 8191: 15 observations
##   predicted class=B4  expected loss=0.2  P(node) =0.00075
##     class counts:     0     1     2    12     0
##    probabilities: 0.000 0.067 0.133 0.800 0.000 
## 
## Node number 10284: 321 observations
##   predicted class=B1  expected loss=0.1619938  P(node) =0.01605
##     class counts:   269    28    19     3     2
##    probabilities: 0.838 0.087 0.059 0.009 0.006 
## 
## Node number 10285: 77 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.2337662  P(node) =0.00385
##     class counts:    59    11     7     0     0
##    probabilities: 0.766 0.143 0.091 0.000 0.000 
##   left son=20570 (70 obs) right son=20571 (7 obs)
##   Primary splits:
##       age               < 86.5   to the left,  improve=4.6987010, (0 missing)
##       depression        < 0.5    to the left,  improve=1.7558440, (0 missing)
##       reimbursement2008 < 385    to the left,  improve=0.6180762, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.1356976, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1272727, (0 missing)
## 
## Node number 10286: 10 observations
##   predicted class=B1  expected loss=0.1  P(node) =0.0005
##     class counts:     9     1     0     0     0
##    probabilities: 0.900 0.100 0.000 0.000 0.000 
## 
## Node number 10287: 22 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.3636364  P(node) =0.0011
##     class counts:    14     7     0     1     0
##    probabilities: 0.636 0.318 0.000 0.045 0.000 
##   left son=20574 (14 obs) right son=20575 (8 obs)
##   Primary splits:
##       age               < 78.5   to the left,  improve=3.13961000, (0 missing)
##       reimbursement2008 < 485    to the right, improve=0.08484848, (0 missing)
##   Surrogate splits:
##       depression < 0.5    to the left,  agree=0.727, adj=0.25, (0 split)
## 
## Node number 11538: 23 observations
##   predicted class=B1  expected loss=0.3478261  P(node) =0.00115
##     class counts:    15     5     3     0     0
##    probabilities: 0.652 0.217 0.130 0.000 0.000 
## 
## Node number 11539: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     2     5     0     0     0
##    probabilities: 0.286 0.714 0.000 0.000 0.000 
## 
## Node number 11798: 8 observations
##   predicted class=B1  expected loss=0.125  P(node) =0.0004
##     class counts:     7     0     1     0     0
##    probabilities: 0.875 0.000 0.125 0.000 0.000 
## 
## Node number 11799: 119 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3277311  P(node) =0.00595
##     class counts:    80    25    11     3     0
##    probabilities: 0.672 0.210 0.092 0.025 0.000 
##   left son=23598 (63 obs) right son=23599 (56 obs)
##   Primary splits:
##       reimbursement2008 < 1125   to the right, improve=0.8342670, (0 missing)
##       depression        < 0.5    to the right, improve=0.6215151, (0 missing)
##       age               < 91     to the right, improve=0.3560924, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.1876751, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1153637, (0 missing)
##   Surrogate splits:
##       age    < 75.5   to the right, agree=0.605, adj=0.161, (0 split)
##       cancer < 0.5    to the left,  agree=0.563, adj=0.071, (0 split)
## 
## Node number 12110: 36 observations,    complexity param=6.084576e-05
##   predicted class=B1  expected loss=0.3888889  P(node) =0.0018
##     class counts:    22    13     1     0     0
##    probabilities: 0.611 0.361 0.028 0.000 0.000 
##   left son=24220 (28 obs) right son=24221 (8 obs)
##   Primary splits:
##       reimbursement2008 < 1005   to the left,  improve=1.2976190, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.9564103, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6806240, (0 missing)
##       age               < 76.5   to the left,  improve=0.2583333, (0 missing)
## 
## Node number 12111: 79 observations,    complexity param=6.084576e-05
##   predicted class=B1  expected loss=0.3544304  P(node) =0.00395
##     class counts:    51    16    11     0     1
##    probabilities: 0.646 0.203 0.139 0.000 0.013 
##   left son=24222 (65 obs) right son=24223 (14 obs)
##   Primary splits:
##       age               < 71.5   to the left,  improve=1.1460840, (0 missing)
##       copd              < 0.5    to the left,  improve=0.8533283, (0 missing)
##       kidney            < 0.5    to the right, improve=0.7541934, (0 missing)
##       depression        < 0.5    to the right, improve=0.7294694, (0 missing)
##       reimbursement2008 < 1075   to the right, improve=0.6940378, (0 missing)
## 
## Node number 12308: 15 observations
##   predicted class=B1  expected loss=0.1333333  P(node) =0.00075
##     class counts:    13     2     0     0     0
##    probabilities: 0.867 0.133 0.000 0.000 0.000 
## 
## Node number 12309: 44 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.4090909  P(node) =0.0022
##     class counts:    26    13     4     0     1
##    probabilities: 0.591 0.295 0.091 0.000 0.023 
##   left son=24618 (16 obs) right son=24619 (28 obs)
##   Primary splits:
##       diabetes          < 0.5    to the right, improve=1.4090910, (0 missing)
##       reimbursement2008 < 1940   to the left,  improve=1.2702020, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.8569674, (0 missing)
##       age               < 52.5   to the right, improve=0.4299242, (0 missing)
##   Surrogate splits:
##       alzheimers < 0.5    to the right, agree=0.75, adj=0.312, (0 split)
## 
## Node number 12336: 11 observations
##   predicted class=B1  expected loss=0.1818182  P(node) =0.00055
##     class counts:     9     2     0     0     0
##    probabilities: 0.818 0.182 0.000 0.000 0.000 
## 
## Node number 12337: 38 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.4473684  P(node) =0.0019
##     class counts:    21    13     4     0     0
##    probabilities: 0.553 0.342 0.105 0.000 0.000 
##   left son=24674 (29 obs) right son=24675 (9 obs)
##   Primary splits:
##       reimbursement2008 < 2020   to the left,  improve=0.85198630, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.59298250, (0 missing)
##       age               < 75.5   to the right, improve=0.46917290, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.21617090, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.04298246, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.789, adj=0.111, (0 split)
## 
## Node number 12724: 32 observations
##   predicted class=B1  expected loss=0.40625  P(node) =0.0016
##     class counts:    19     6     6     0     1
##    probabilities: 0.594 0.188 0.188 0.000 0.031 
## 
## Node number 12725: 13 observations
##   predicted class=B2  expected loss=0.4615385  P(node) =0.00065
##     class counts:     4     7     2     0     0
##    probabilities: 0.308 0.538 0.154 0.000 0.000 
## 
## Node number 12726: 36 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.5555556  P(node) =0.0018
##     class counts:    16    10     8     2     0
##    probabilities: 0.444 0.278 0.222 0.056 0.000 
##   left son=25452 (12 obs) right son=25453 (24 obs)
##   Primary splits:
##       reimbursement2008 < 2400   to the left,  improve=1.3055560, (0 missing)
##       age               < 67.5   to the left,  improve=1.1014790, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8040404, (0 missing)
##       depression        < 0.5    to the right, improve=0.5472222, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.4126984, (0 missing)
##   Surrogate splits:
##       osteoporosis < 0.5    to the right, agree=0.694, adj=0.083, (0 split)
## 
## Node number 12727: 24 observations
##   predicted class=B2  expected loss=0.4166667  P(node) =0.0012
##     class counts:     5    14     5     0     0
##    probabilities: 0.208 0.583 0.208 0.000 0.000 
## 
## Node number 13340: 34 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.4411765  P(node) =0.0017
##     class counts:    19    14     1     0     0
##    probabilities: 0.559 0.412 0.029 0.000 0.000 
##   left son=26680 (7 obs) right son=26681 (27 obs)
##   Primary splits:
##       reimbursement2008 < 2070   to the right, improve=0.96389670, (0 missing)
##       age               < 79.5   to the right, improve=0.48151590, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.41515840, (0 missing)
##       kidney            < 0.5    to the left,  improve=0.41515840, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.06900452, (0 missing)
## 
## Node number 13341: 8 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0004
##     class counts:     2     4     1     1     0
##    probabilities: 0.250 0.500 0.125 0.125 0.000 
## 
## Node number 13378: 20 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.001
##     class counts:    15     5     0     0     0
##    probabilities: 0.750 0.250 0.000 0.000 0.000 
## 
## Node number 13379: 95 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.4842105  P(node) =0.00475
##     class counts:    49    27    11     7     1
##    probabilities: 0.516 0.284 0.116 0.074 0.011 
##   left son=26758 (27 obs) right son=26759 (68 obs)
##   Primary splits:
##       reimbursement2008 < 1735   to the left,  improve=2.2624360, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6768740, (0 missing)
##       age               < 67.5   to the left,  improve=0.6566828, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5342853, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.1812826, (0 missing)
## 
## Node number 13408: 55 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.5272727  P(node) =0.00275
##     class counts:    26    24     2     3     0
##    probabilities: 0.473 0.436 0.036 0.055 0.000 
##   left son=26816 (45 obs) right son=26817 (10 obs)
##   Primary splits:
##       reimbursement2008 < 1865   to the left,  improve=1.1555560, (0 missing)
##       age               < 66.5   to the right, improve=1.0879120, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4500000, (0 missing)
##       kidney            < 0.5    to the right, improve=0.3837209, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.3285714, (0 missing)
## 
## Node number 13409: 33 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5151515  P(node) =0.00165
##     class counts:    10    16     4     2     1
##    probabilities: 0.303 0.485 0.121 0.061 0.030 
##   left son=26818 (7 obs) right son=26819 (26 obs)
##   Primary splits:
##       age               < 72.5   to the right, improve=1.6307030, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.0479800, (0 missing)
##       reimbursement2008 < 1980   to the right, improve=0.9393939, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.8163591, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.5449883, (0 missing)
## 
## Node number 13702: 14 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.0007
##     class counts:    10     4     0     0     0
##    probabilities: 0.714 0.286 0.000 0.000 0.000 
## 
## Node number 13703: 10 observations
##   predicted class=B2  expected loss=0.4  P(node) =0.0005
##     class counts:     2     6     1     1     0
##    probabilities: 0.200 0.600 0.100 0.100 0.000 
## 
## Node number 13740: 7 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.00035
##     class counts:     5     0     2     0     0
##    probabilities: 0.714 0.000 0.286 0.000 0.000 
## 
## Node number 13741: 39 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.5128205  P(node) =0.00195
##     class counts:    14    19     6     0     0
##    probabilities: 0.359 0.487 0.154 0.000 0.000 
##   left son=27482 (15 obs) right son=27483 (24 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the right, improve=2.1782050, (0 missing)
##       reimbursement2008 < 2225   to the left,  improve=0.9035674, (0 missing)
##       diabetes          < 0.5    to the right, improve=0.5156510, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.4871795, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4102564, (0 missing)
##   Surrogate splits:
##       age    < 81.5   to the right, agree=0.692, adj=0.200, (0 split)
##       stroke < 0.5    to the right, agree=0.641, adj=0.067, (0 split)
## 
## Node number 13742: 13 observations
##   predicted class=B1  expected loss=0.4615385  P(node) =0.00065
##     class counts:     7     6     0     0     0
##    probabilities: 0.538 0.462 0.000 0.000 0.000 
## 
## Node number 13743: 40 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.375  P(node) =0.002
##     class counts:     6    25     8     1     0
##    probabilities: 0.150 0.625 0.200 0.025 0.000 
##   left son=27486 (33 obs) right son=27487 (7 obs)
##   Primary splits:
##       age               < 78.5   to the left,  improve=1.5816020, (0 missing)
##       reimbursement2008 < 1955   to the left,  improve=1.1595240, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.1595240, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5166667, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.4983516, (0 missing)
## 
## Node number 13868: 30 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4666667  P(node) =0.0015
##     class counts:    16    11     3     0     0
##    probabilities: 0.533 0.367 0.100 0.000 0.000 
##   left son=27736 (22 obs) right son=27737 (8 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=1.3151520, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7696970, (0 missing)
##       reimbursement2008 < 2845   to the left,  improve=0.6333333, (0 missing)
##       age               < 73.5   to the left,  improve=0.2464555, (0 missing)
##       bucket2008        < 1.5    to the right, improve=0.2126984, (0 missing)
##   Surrogate splits:
##       copd              < 0.5    to the left,  agree=0.867, adj=0.500, (0 split)
##       reimbursement2008 < 3015   to the left,  agree=0.867, adj=0.500, (0 split)
##       bucket2008        < 1.5    to the left,  agree=0.833, adj=0.375, (0 split)
## 
## Node number 13869: 11 observations
##   predicted class=B2  expected loss=0.4545455  P(node) =0.00055
##     class counts:     2     6     3     0     0
##    probabilities: 0.182 0.545 0.273 0.000 0.000 
## 
## Node number 13874: 24 observations
##   predicted class=B1  expected loss=0.375  P(node) =0.0012
##     class counts:    15     3     5     0     1
##    probabilities: 0.625 0.125 0.208 0.000 0.042 
## 
## Node number 13875: 27 observations,    complexity param=0.0001014096
##   predicted class=B1  expected loss=0.5925926  P(node) =0.00135
##     class counts:    11     8     5     2     1
##    probabilities: 0.407 0.296 0.185 0.074 0.037 
##   left son=27750 (20 obs) right son=27751 (7 obs)
##   Primary splits:
##       reimbursement2008 < 3040   to the right, improve=1.3798940, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.1664490, (0 missing)
##       age               < 75.5   to the right, improve=0.8791423, (0 missing)
##       depression        < 0.5    to the right, improve=0.1656085, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1481481, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the right, agree=0.926, adj=0.714, (0 split)
## 
## Node number 13876: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     2     5     0     0     0
##    probabilities: 0.286 0.714 0.000 0.000 0.000 
## 
## Node number 13877: 26 observations,    complexity param=0.0002662002
##   predicted class=B1  expected loss=0.5769231  P(node) =0.0013
##     class counts:    11    10     4     1     0
##    probabilities: 0.423 0.385 0.154 0.038 0.000 
##   left son=27754 (12 obs) right son=27755 (14 obs)
##   Primary splits:
##       reimbursement2008 < 2785   to the left,  improve=1.203297, (0 missing)
##       bucket2008        < 1.5    to the right, improve=1.040598, (0 missing)
##       age               < 82.5   to the left,  improve=0.707265, (0 missing)
##   Surrogate splits:
##       bucket2008 < 1.5    to the left,  agree=0.769, adj=0.500, (0 split)
##       depression < 0.5    to the right, agree=0.615, adj=0.167, (0 split)
##       age        < 81     to the left,  agree=0.577, adj=0.083, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.577, adj=0.083, (0 split)
## 
## Node number 13962: 23 observations,    complexity param=0.000253524
##   predicted class=B2  expected loss=0.5217391  P(node) =0.00115
##     class counts:    10    11     1     1     0
##    probabilities: 0.435 0.478 0.043 0.043 0.000 
##   left son=27924 (9 obs) right son=27925 (14 obs)
##   Primary splits:
##       reimbursement2008 < 2630   to the left,  improve=1.8599030, (0 missing)
##       age               < 71.5   to the right, improve=1.5186340, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7505017, (0 missing)
##   Surrogate splits:
##       age < 71.5   to the left,  agree=0.652, adj=0.111, (0 split)
## 
## Node number 13963: 21 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4761905  P(node) =0.00105
##     class counts:    11     5     2     3     0
##    probabilities: 0.524 0.238 0.095 0.143 0.000 
##   left son=27926 (12 obs) right son=27927 (9 obs)
##   Primary splits:
##       age               < 71.5   to the right, improve=1.2619050, (0 missing)
##       depression        < 0.5    to the right, improve=0.5714286, (0 missing)
##       reimbursement2008 < 2850   to the right, improve=0.1428571, (0 missing)
##   Surrogate splits:
##       copd              < 0.5    to the left,  agree=0.619, adj=0.111, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.619, adj=0.111, (0 split)
##       reimbursement2008 < 2830   to the left,  agree=0.619, adj=0.111, (0 split)
## 
## Node number 13966: 10 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0005
##     class counts:     5     3     1     1     0
##    probabilities: 0.500 0.300 0.100 0.100 0.000 
## 
## Node number 13967: 35 observations
##   predicted class=B2  expected loss=0.3714286  P(node) =0.00175
##     class counts:     7    22     3     3     0
##    probabilities: 0.200 0.629 0.086 0.086 0.000 
## 
## Node number 14010: 8 observations
##   predicted class=B1  expected loss=0.375  P(node) =0.0004
##     class counts:     5     2     1     0     0
##    probabilities: 0.625 0.250 0.125 0.000 0.000 
## 
## Node number 14011: 12 observations
##   predicted class=B3  expected loss=0.6666667  P(node) =0.0006
##     class counts:     3     1     4     4     0
##    probabilities: 0.250 0.083 0.333 0.333 0.000 
## 
## Node number 14080: 18 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0009
##     class counts:    12     4     2     0     0
##    probabilities: 0.667 0.222 0.111 0.000 0.000 
## 
## Node number 14081: 14 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0007
##     class counts:     5     7     2     0     0
##    probabilities: 0.357 0.500 0.143 0.000 0.000 
## 
## Node number 14388: 32 observations
##   predicted class=B1  expected loss=0.4375  P(node) =0.0016
##     class counts:    18    11     2     1     0
##    probabilities: 0.562 0.344 0.062 0.031 0.000 
## 
## Node number 14389: 47 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4042553  P(node) =0.00235
##     class counts:    28     6    13     0     0
##    probabilities: 0.596 0.128 0.277 0.000 0.000 
##   left son=28778 (22 obs) right son=28779 (25 obs)
##   Primary splits:
##       age               < 70.5   to the right, improve=1.1429010, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9358252, (0 missing)
##       reimbursement2008 < 4425   to the right, improve=0.5714819, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.4947017, (0 missing)
##       kidney            < 0.5    to the right, improve=0.3933442, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 5070   to the left,  agree=0.596, adj=0.136, (0 split)
##       alzheimers        < 0.5    to the right, agree=0.574, adj=0.091, (0 split)
##       kidney            < 0.5    to the left,  agree=0.553, adj=0.045, (0 split)
## 
## Node number 15372: 20 observations
##   predicted class=B1  expected loss=0.3  P(node) =0.001
##     class counts:    14     3     2     1     0
##    probabilities: 0.700 0.150 0.100 0.050 0.000 
## 
## Node number 15373: 56 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5535714  P(node) =0.0028
##     class counts:    25    14    16     1     0
##    probabilities: 0.446 0.250 0.286 0.018 0.000 
##   left son=30746 (17 obs) right son=30747 (39 obs)
##   Primary splits:
##       reimbursement2008 < 3745   to the left,  improve=1.6851430, (0 missing)
##       ihd               < 0.5    to the left,  improve=1.1778070, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.5569382, (0 missing)
##       age               < 53.5   to the right, improve=0.4621212, (0 missing)
##       depression        < 0.5    to the left,  improve=0.1055556, (0 missing)
##   Surrogate splits:
##       age < 69.5   to the right, agree=0.714, adj=0.059, (0 split)
## 
## Node number 15426: 85 observations,    complexity param=0.0003295812
##   predicted class=B1  expected loss=0.4588235  P(node) =0.00425
##     class counts:    46    28    10     1     0
##    probabilities: 0.541 0.329 0.118 0.012 0.000 
##   left son=30852 (76 obs) right son=30853 (9 obs)
##   Primary splits:
##       reimbursement2008 < 29020  to the left,  improve=1.3666320, (0 missing)
##       age               < 82.5   to the left,  improve=0.8676149, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.4882353, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.3426025, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.3141176, (0 missing)
##   Surrogate splits:
##       bucket2008 < 4.5    to the left,  agree=0.918, adj=0.222, (0 split)
## 
## Node number 15427: 21 observations,    complexity param=0.0003295812
##   predicted class=B1  expected loss=0.6666667  P(node) =0.00105
##     class counts:     7     7     1     6     0
##    probabilities: 0.333 0.333 0.048 0.286 0.000 
##   left son=30854 (13 obs) right son=30855 (8 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=1.2060440, (0 missing)
##       reimbursement2008 < 5580   to the left,  improve=0.7637363, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4285714, (0 missing)
##       age               < 79.5   to the right, improve=0.2936508, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1428571, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 5580   to the left,  agree=0.810, adj=0.500, (0 split)
##       stroke            < 0.5    to the left,  agree=0.714, adj=0.250, (0 split)
##       age               < 83.5   to the left,  agree=0.667, adj=0.125, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.667, adj=0.125, (0 split)
## 
## Node number 15450: 26 observations
##   predicted class=B2  expected loss=0.1923077  P(node) =0.0013
##     class counts:     3    21     2     0     0
##    probabilities: 0.115 0.808 0.077 0.000 0.000 
## 
## Node number 15451: 21 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5238095  P(node) =0.00105
##     class counts:     4    10     5     2     0
##    probabilities: 0.190 0.476 0.238 0.095 0.000 
##   left son=30902 (10 obs) right son=30903 (11 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.0406930, (0 missing)
##       reimbursement2008 < 10445  to the right, improve=0.2380952, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.1861472, (0 missing)
##       age               < 86.5   to the right, improve=0.1721612, (0 missing)
##   Surrogate splits:
##       age               < 86.5   to the right, agree=0.714, adj=0.4, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.619, adj=0.2, (0 split)
##       reimbursement2008 < 5600   to the left,  agree=0.619, adj=0.2, (0 split)
## 
## Node number 15452: 38 observations,    complexity param=0.0004056384
##   predicted class=B1  expected loss=0.6052632  P(node) =0.0019
##     class counts:    15    13     5     5     0
##    probabilities: 0.395 0.342 0.132 0.132 0.000 
##   left son=30904 (26 obs) right son=30905 (12 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the right, improve=1.3927130, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=1.2562660, (0 missing)
##       copd              < 0.5    to the left,  improve=1.1773280, (0 missing)
##       age               < 78.5   to the right, improve=0.7975822, (0 missing)
##       reimbursement2008 < 21895  to the left,  improve=0.5716817, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 7780   to the right, agree=0.763, adj=0.250, (0 split)
##       bucket2008        < 2.5    to the right, agree=0.737, adj=0.167, (0 split)
## 
## Node number 15453: 11 observations
##   predicted class=B2  expected loss=0.4545455  P(node) =0.00055
##     class counts:     0     6     2     2     1
##    probabilities: 0.000 0.545 0.182 0.182 0.091 
## 
## Node number 15482: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     2     2     3     0     0
##    probabilities: 0.286 0.286 0.429 0.000 0.000 
## 
## Node number 15483: 13 observations
##   predicted class=B2  expected loss=0.4615385  P(node) =0.00065
##     class counts:     3     7     1     2     0
##    probabilities: 0.231 0.538 0.077 0.154 0.000 
## 
## Node number 15574: 8 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0004
##     class counts:     1     4     2     1     0
##    probabilities: 0.125 0.500 0.250 0.125 0.000 
## 
## Node number 15575: 14 observations
##   predicted class=B3  expected loss=0.3571429  P(node) =0.0007
##     class counts:     1     3     9     1     0
##    probabilities: 0.071 0.214 0.643 0.071 0.000 
## 
## Node number 15576: 16 observations
##   predicted class=B3  expected loss=0.625  P(node) =0.0008
##     class counts:     5     5     6     0     0
##    probabilities: 0.312 0.312 0.375 0.000 0.000 
## 
## Node number 15577: 10 observations
##   predicted class=B2  expected loss=0.6  P(node) =0.0005
##     class counts:     1     4     3     2     0
##    probabilities: 0.100 0.400 0.300 0.200 0.000 
## 
## Node number 15762: 32 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5625  P(node) =0.0016
##     class counts:    12    14     3     2     1
##    probabilities: 0.375 0.438 0.094 0.062 0.031 
##   left son=31524 (8 obs) right son=31525 (24 obs)
##   Primary splits:
##       ihd               < 0.5    to the left,  improve=2.0208330, (0 missing)
##       reimbursement2008 < 5625   to the left,  improve=1.1806370, (0 missing)
##       age               < 67     to the left,  improve=0.8541667, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6943627, (0 missing)
##       copd              < 0.5    to the left,  improve=0.6344697, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 5120   to the left,  agree=0.781, adj=0.125, (0 split)
## 
## Node number 15763: 20 observations
##   predicted class=B2  expected loss=0.25  P(node) =0.001
##     class counts:     2    15     2     1     0
##    probabilities: 0.100 0.750 0.100 0.050 0.000 
## 
## Node number 15826: 12 observations
##   predicted class=B2  expected loss=0.4166667  P(node) =0.0006
##     class counts:     2     7     3     0     0
##    probabilities: 0.167 0.583 0.250 0.000 0.000 
## 
## Node number 15827: 10 observations
##   predicted class=B3  expected loss=0.5  P(node) =0.0005
##     class counts:     3     1     5     1     0
##    probabilities: 0.300 0.100 0.500 0.100 0.000 
## 
## Node number 15828: 53 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5283019  P(node) =0.00265
##     class counts:    14    25     7     6     1
##    probabilities: 0.264 0.472 0.132 0.113 0.019 
##   left son=31656 (10 obs) right son=31657 (43 obs)
##   Primary splits:
##       copd              < 0.5    to the right, improve=1.6914440, (0 missing)
##       age               < 84.5   to the right, improve=1.2423480, (0 missing)
##       reimbursement2008 < 4140   to the right, improve=1.2035630, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.4599632, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.4325067, (0 missing)
##   Surrogate splits:
##       age < 85.5   to the right, agree=0.83, adj=0.1, (0 split)
## 
## Node number 15829: 37 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5135135  P(node) =0.00185
##     class counts:     4    18    13     2     0
##    probabilities: 0.108 0.486 0.351 0.054 0.000 
##   left son=31658 (15 obs) right son=31659 (22 obs)
##   Primary splits:
##       age               < 74.5   to the right, improve=2.4139230, (0 missing)
##       reimbursement2008 < 9285   to the left,  improve=0.9525955, (0 missing)
##       copd              < 0.5    to the right, improve=0.9323379, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.6526177, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.4084271, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 8600   to the right, agree=0.649, adj=0.133, (0 split)
##       cancer            < 0.5    to the right, agree=0.622, adj=0.067, (0 split)
## 
## Node number 15830: 46 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5869565  P(node) =0.0023
##     class counts:     7    19    18     2     0
##    probabilities: 0.152 0.413 0.391 0.043 0.000 
##   left son=31660 (10 obs) right son=31661 (36 obs)
##   Primary splits:
##       reimbursement2008 < 5620   to the left,  improve=1.5787440, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.4489460, (0 missing)
##       bucket2008        < 2.5    to the right, improve=1.2212840, (0 missing)
##       age               < 72.5   to the left,  improve=0.6469979, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5652174, (0 missing)
## 
## Node number 15831: 28 observations,    complexity param=0.0002281716
##   predicted class=B1  expected loss=0.6785714  P(node) =0.0014
##     class counts:     9     6     8     4     1
##    probabilities: 0.321 0.214 0.286 0.143 0.036 
##   left son=31662 (9 obs) right son=31663 (19 obs)
##   Primary splits:
##       age               < 84.5   to the left,  improve=2.6829570, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=1.8841270, (0 missing)
##       reimbursement2008 < 9375   to the left,  improve=1.4047620, (0 missing)
##       copd              < 0.5    to the left,  improve=1.1730160, (0 missing)
##       ihd               < 0.5    to the right, improve=0.6785714, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 11245  to the right, agree=0.75, adj=0.222, (0 split)
## 
## Node number 15876: 13 observations
##   predicted class=B1  expected loss=0.5384615  P(node) =0.00065
##     class counts:     6     3     4     0     0
##    probabilities: 0.462 0.231 0.308 0.000 0.000 
## 
## Node number 15877: 11 observations
##   predicted class=B2  expected loss=0.5454545  P(node) =0.00055
##     class counts:     1     5     5     0     0
##    probabilities: 0.091 0.455 0.455 0.000 0.000 
## 
## Node number 15896: 24 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.5416667  P(node) =0.0012
##     class counts:    11     6     1     5     1
##    probabilities: 0.458 0.250 0.042 0.208 0.042 
##   left son=31792 (10 obs) right son=31793 (14 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=2.3904760, (0 missing)
##       reimbursement2008 < 8475   to the left,  improve=0.7083333, (0 missing)
##       age               < 76.5   to the left,  improve=0.7047619, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7047619, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.5291375, (0 missing)
##   Surrogate splits:
##       alzheimers        < 0.5    to the right, agree=0.708, adj=0.3, (0 split)
##       depression        < 0.5    to the right, agree=0.667, adj=0.2, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.667, adj=0.2, (0 split)
##       reimbursement2008 < 8545   to the left,  agree=0.625, adj=0.1, (0 split)
## 
## Node number 15897: 145 observations,    complexity param=0.0002738059
##   predicted class=B2  expected loss=0.5655172  P(node) =0.00725
##     class counts:    32    63    20    26     4
##    probabilities: 0.221 0.434 0.138 0.179 0.028 
##   left son=31794 (18 obs) right son=31795 (127 obs)
##   Primary splits:
##       stroke            < 0.5    to the right, improve=1.3643170, (0 missing)
##       age               < 69.5   to the right, improve=1.3391670, (0 missing)
##       reimbursement2008 < 12310  to the left,  improve=1.0866570, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.7151354, (0 missing)
##       depression        < 0.5    to the right, improve=0.5171751, (0 missing)
## 
## Node number 15900: 10 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0005
##     class counts:     2     5     2     0     1
##    probabilities: 0.200 0.500 0.200 0.000 0.100 
## 
## Node number 15901: 24 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.625  P(node) =0.0012
##     class counts:     7     3     9     4     1
##    probabilities: 0.292 0.125 0.375 0.167 0.042 
##   left son=31802 (17 obs) right son=31803 (7 obs)
##   Primary splits:
##       cancer            < 0.5    to the left,  improve=1.3823530, (0 missing)
##       reimbursement2008 < 10140  to the left,  improve=1.3181820, (0 missing)
##       depression        < 0.5    to the left,  improve=0.3333333, (0 missing)
##       age               < 82.5   to the left,  improve=0.3000000, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1153846, (0 missing)
##   Surrogate splits:
##       age               < 78.5   to the right, agree=0.792, adj=0.286, (0 split)
##       reimbursement2008 < 12480  to the left,  agree=0.750, adj=0.143, (0 split)
## 
## Node number 15902: 38 observations,    complexity param=7.60572e-05
##   predicted class=B2  expected loss=0.4736842  P(node) =0.0019
##     class counts:     3    20    10     5     0
##    probabilities: 0.079 0.526 0.263 0.132 0.000 
##   left son=31804 (23 obs) right son=31805 (15 obs)
##   Primary splits:
##       reimbursement2008 < 13070  to the left,  improve=1.5183830, (0 missing)
##       depression        < 0.5    to the right, improve=0.6842105, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5789474, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.3616541, (0 missing)
##       age               < 81.5   to the left,  improve=0.3395253, (0 missing)
##   Surrogate splits:
##       depression < 0.5    to the right, agree=0.632, adj=0.067, (0 split)
## 
## Node number 15903: 19 observations
##   predicted class=B4  expected loss=0.5263158  P(node) =0.00095
##     class counts:     2     4     3     9     1
##    probabilities: 0.105 0.211 0.158 0.474 0.053 
## 
## Node number 15920: 25 observations,    complexity param=0.0003650745
##   predicted class=B2  expected loss=0.6  P(node) =0.00125
##     class counts:     8    10     3     3     1
##    probabilities: 0.320 0.400 0.120 0.120 0.040 
##   left son=31840 (12 obs) right son=31841 (13 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the right, improve=2.974872, (0 missing)
##       reimbursement2008 < 5050   to the right, improve=2.154359, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=1.596667, (0 missing)
##       copd              < 0.5    to the left,  improve=1.546667, (0 missing)
##       age               < 84.5   to the left,  improve=0.654359, (0 missing)
##   Surrogate splits:
##       age               < 83.5   to the left,  agree=0.64, adj=0.250, (0 split)
##       copd              < 0.5    to the left,  agree=0.64, adj=0.250, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.64, adj=0.250, (0 split)
##       reimbursement2008 < 5050   to the left,  agree=0.64, adj=0.250, (0 split)
##       cancer            < 0.5    to the right, agree=0.60, adj=0.167, (0 split)
## 
## Node number 15921: 23 observations
##   predicted class=B2  expected loss=0.3478261  P(node) =0.00115
##     class counts:     1    15     4     3     0
##    probabilities: 0.043 0.652 0.174 0.130 0.000 
## 
## Node number 15922: 94 observations,    complexity param=0.0003650745
##   predicted class=B2  expected loss=0.5744681  P(node) =0.0047
##     class counts:    22    40    17    13     2
##    probabilities: 0.234 0.426 0.181 0.138 0.021 
##   left son=31844 (47 obs) right son=31845 (47 obs)
##   Primary splits:
##       reimbursement2008 < 4080   to the left,  improve=2.3617020, (0 missing)
##       age               < 59.5   to the left,  improve=0.9410374, (0 missing)
##       copd              < 0.5    to the right, improve=0.7460624, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.7348936, (0 missing)
##       ihd               < 0.5    to the right, improve=0.5315420, (0 missing)
##   Surrogate splits:
##       depression    < 0.5    to the left,  agree=0.638, adj=0.277, (0 split)
##       copd          < 0.5    to the right, agree=0.628, adj=0.255, (0 split)
##       cancer        < 0.5    to the left,  agree=0.564, adj=0.128, (0 split)
##       age           < 59.5   to the left,  agree=0.553, adj=0.106, (0 split)
##       heart.failure < 0.5    to the left,  agree=0.553, adj=0.106, (0 split)
## 
## Node number 15923: 68 observations,    complexity param=0.0003650745
##   predicted class=B3  expected loss=0.6617647  P(node) =0.0034
##     class counts:    13    18    23    12     2
##    probabilities: 0.191 0.265 0.338 0.176 0.029 
##   left son=31846 (39 obs) right son=31847 (29 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=2.0284240, (0 missing)
##       reimbursement2008 < 5310   to the left,  improve=1.4514850, (0 missing)
##       depression        < 0.5    to the right, improve=1.3449950, (0 missing)
##       age               < 76.5   to the right, improve=1.1528720, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.6729055, (0 missing)
##   Surrogate splits:
##       age               < 75.5   to the right, agree=0.632, adj=0.138, (0 split)
##       stroke            < 0.5    to the left,  agree=0.618, adj=0.103, (0 split)
##       reimbursement2008 < 5600   to the left,  agree=0.618, adj=0.103, (0 split)
##       ihd               < 0.5    to the right, agree=0.588, adj=0.034, (0 split)
## 
## Node number 16036: 22 observations,    complexity param=0.0001014096
##   predicted class=B2  expected loss=0.4545455  P(node) =0.0011
##     class counts:     9    12     1     0     0
##    probabilities: 0.409 0.545 0.045 0.000 0.000 
##   left son=32072 (7 obs) right son=32073 (15 obs)
##   Primary splits:
##       reimbursement2008 < 3905   to the left,  improve=1.0606060, (0 missing)
##       depression        < 0.5    to the left,  improve=0.9772727, (0 missing)
##       age               < 70     to the right, improve=0.4701299, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.1201299, (0 missing)
## 
## Node number 16037: 7 observations
##   predicted class=B2  expected loss=0.7142857  P(node) =0.00035
##     class counts:     1     2     2     2     0
##    probabilities: 0.143 0.286 0.286 0.286 0.000 
## 
## Node number 16038: 31 observations
##   predicted class=B2  expected loss=0.3548387  P(node) =0.00155
##     class counts:     3    20     5     2     1
##    probabilities: 0.097 0.645 0.161 0.065 0.032 
## 
## Node number 16039: 9 observations
##   predicted class=B3  expected loss=0.4444444  P(node) =0.00045
##     class counts:     1     2     5     1     0
##    probabilities: 0.111 0.222 0.556 0.111 0.000 
## 
## Node number 16106: 130 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5  P(node) =0.0065
##     class counts:    13    65    36    14     2
##    probabilities: 0.100 0.500 0.277 0.108 0.015 
##   left son=32212 (52 obs) right son=32213 (78 obs)
##   Primary splits:
##       reimbursement2008 < 10630  to the right, improve=1.0128210, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.7109522, (0 missing)
##       age               < 95.5   to the right, improve=0.6226356, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.4532726, (0 missing)
##       depression        < 0.5    to the left,  improve=0.3446886, (0 missing)
##   Surrogate splits:
##       age < 96.5   to the right, agree=0.608, adj=0.019, (0 split)
## 
## Node number 16107: 22 observations,    complexity param=0.0001521144
##   predicted class=B3  expected loss=0.5454545  P(node) =0.0011
##     class counts:     0     8    10     2     2
##    probabilities: 0.000 0.364 0.455 0.091 0.091 
##   left son=32214 (14 obs) right son=32215 (8 obs)
##   Primary splits:
##       reimbursement2008 < 14005  to the right, improve=1.5032470, (0 missing)
##       age               < 70     to the left,  improve=0.8142968, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.6151515, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5484848, (0 missing)
##       depression        < 0.5    to the right, improve=0.4318182, (0 missing)
##   Surrogate splits:
##       stroke < 0.5    to the left,  agree=0.682, adj=0.125, (0 split)
## 
## Node number 16258: 41 observations,    complexity param=0.000380286
##   predicted class=B1  expected loss=0.6341463  P(node) =0.00205
##     class counts:    15     7     9    10     0
##    probabilities: 0.366 0.171 0.220 0.244 0.000 
##   left son=32516 (23 obs) right son=32517 (18 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=2.0715210, (0 missing)
##       age               < 74.5   to the right, improve=1.6679890, (0 missing)
##       cancer            < 0.5    to the right, improve=1.0314710, (0 missing)
##       reimbursement2008 < 24805  to the right, improve=0.9024390, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4716698, (0 missing)
##   Surrogate splits:
##       age               < 78.5   to the left,  agree=0.610, adj=0.111, (0 split)
##       reimbursement2008 < 24395  to the left,  agree=0.610, adj=0.111, (0 split)
##       alzheimers        < 0.5    to the right, agree=0.585, adj=0.056, (0 split)
## 
## Node number 16259: 8 observations
##   predicted class=B4  expected loss=0.375  P(node) =0.0004
##     class counts:     1     0     2     5     0
##    probabilities: 0.125 0.000 0.250 0.625 0.000 
## 
## Node number 16280: 28 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.0014
##     class counts:     5    16     3     3     1
##    probabilities: 0.179 0.571 0.107 0.107 0.036 
## 
## Node number 16281: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     0     1     3     2     1
##    probabilities: 0.000 0.143 0.429 0.286 0.143 
## 
## Node number 16282: 39 observations,    complexity param=0.000380286
##   predicted class=B2  expected loss=0.7179487  P(node) =0.00195
##     class counts:     9    11     9     9     1
##    probabilities: 0.231 0.282 0.231 0.231 0.026 
##   left son=32564 (10 obs) right son=32565 (29 obs)
##   Primary splits:
##       age               < 80     to the left,  improve=1.7168880, (0 missing)
##       reimbursement2008 < 17795  to the right, improve=0.9267399, (0 missing)
##       stroke            < 0.5    to the left,  improve=0.8587676, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4467399, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3426385, (0 missing)
##   Surrogate splits:
##       heart.failure < 0.5    to the left,  agree=0.769, adj=0.1, (0 split)
## 
## Node number 16283: 7 observations
##   predicted class=B4  expected loss=0.4285714  P(node) =0.00035
##     class counts:     0     0     3     4     0
##    probabilities: 0.000 0.000 0.429 0.571 0.000 
## 
## Node number 16288: 22 observations
##   predicted class=B2  expected loss=0.3636364  P(node) =0.0011
##     class counts:     2    14     6     0     0
##    probabilities: 0.091 0.636 0.273 0.000 0.000 
## 
## Node number 16289: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     1     2     3     0     1
##    probabilities: 0.143 0.286 0.429 0.000 0.143 
## 
## Node number 16292: 20 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.55  P(node) =0.001
##     class counts:     9     4     4     3     0
##    probabilities: 0.450 0.200 0.200 0.150 0.000 
##   left son=32584 (10 obs) right son=32585 (10 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=1.9000000, (0 missing)
##       copd              < 0.5    to the left,  improve=1.8166670, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=1.2186810, (0 missing)
##       reimbursement2008 < 18105  to the left,  improve=0.8166667, (0 missing)
##       age               < 79     to the left,  improve=0.5000000, (0 missing)
##   Surrogate splits:
##       alzheimers        < 0.5    to the right, agree=0.65, adj=0.3, (0 split)
##       reimbursement2008 < 18235  to the left,  agree=0.65, adj=0.3, (0 split)
##       age               < 93.5   to the right, agree=0.60, adj=0.2, (0 split)
##       copd              < 0.5    to the right, agree=0.60, adj=0.2, (0 split)
##       cancer            < 0.5    to the left,  agree=0.55, adj=0.1, (0 split)
## 
## Node number 16293: 35 observations
##   predicted class=B2  expected loss=0.4857143  P(node) =0.00175
##     class counts:     4    18     5     6     2
##    probabilities: 0.114 0.514 0.143 0.171 0.057 
## 
## Node number 16294: 9 observations
##   predicted class=B2  expected loss=0.2222222  P(node) =0.00045
##     class counts:     0     7     2     0     0
##    probabilities: 0.000 0.778 0.222 0.000 0.000 
## 
## Node number 16295: 25 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.68  P(node) =0.00125
##     class counts:     0     8     8     7     2
##    probabilities: 0.000 0.320 0.320 0.280 0.080 
##   left son=32590 (10 obs) right son=32591 (15 obs)
##   Primary splits:
##       age               < 82.5   to the left,  improve=1.0933330, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.8933333, (0 missing)
##       reimbursement2008 < 16595  to the right, improve=0.6171429, (0 missing)
##       depression        < 0.5    to the left,  improve=0.1885714, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.1276471, (0 missing)
##   Surrogate splits:
##       cancer            < 0.5    to the right, agree=0.68, adj=0.2, (0 split)
##       copd              < 0.5    to the right, agree=0.68, adj=0.2, (0 split)
##       reimbursement2008 < 17140  to the right, agree=0.68, adj=0.2, (0 split)
## 
## Node number 16374: 39 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5128205  P(node) =0.00195
##     class counts:     0    19     3    17     0
##    probabilities: 0.000 0.487 0.077 0.436 0.000 
##   left son=32748 (26 obs) right son=32749 (13 obs)
##   Primary splits:
##       age               < 63.5   to the right, improve=0.9487179, (0 missing)
##       reimbursement2008 < 43555  to the left,  improve=0.6509512, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5692308, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.3145206, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2601728, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 40920  to the right, agree=0.744, adj=0.231, (0 split)
## 
## Node number 16375: 19 observations
##   predicted class=B2  expected loss=0.7368421  P(node) =0.00095
##     class counts:     0     5     4     5     5
##    probabilities: 0.000 0.263 0.211 0.263 0.263 
## 
## Node number 16376: 139 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6546763  P(node) =0.00695
##     class counts:    14    48    36    36     5
##    probabilities: 0.101 0.345 0.259 0.259 0.036 
##   left son=32752 (7 obs) right son=32753 (132 obs)
##   Primary splits:
##       reimbursement2008 < 79435  to the right, improve=1.587483, (0 missing)
##       age               < 68.5   to the right, improve=1.331578, (0 missing)
##       bucket2008        < 4.5    to the right, improve=1.092884, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.060491, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.026367, (0 missing)
## 
## Node number 16377: 11 observations
##   predicted class=B3  expected loss=0.4545455  P(node) =0.00055
##     class counts:     0     1     6     2     2
##    probabilities: 0.000 0.091 0.545 0.182 0.182 
## 
## Node number 16378: 9 observations
##   predicted class=B3  expected loss=0.5555556  P(node) =0.00045
##     class counts:     0     2     4     2     1
##    probabilities: 0.000 0.222 0.444 0.222 0.111 
## 
## Node number 16379: 21 observations,    complexity param=0.0001521144
##   predicted class=B4  expected loss=0.4761905  P(node) =0.00105
##     class counts:     0     3     7    11     0
##    probabilities: 0.000 0.143 0.333 0.524 0.000 
##   left son=32758 (10 obs) right son=32759 (11 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=0.8580087, (0 missing)
##       age               < 85.5   to the left,  improve=0.5317460, (0 missing)
##       reimbursement2008 < 49045  to the left,  improve=0.4398268, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.2261905, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.1904762, (0 missing)
##   Surrogate splits:
##       cancer            < 0.5    to the right, agree=0.810, adj=0.6, (0 split)
##       arthritis         < 0.5    to the right, agree=0.667, adj=0.3, (0 split)
##       reimbursement2008 < 42665  to the left,  agree=0.619, adj=0.2, (0 split)
##       age               < 83.5   to the left,  agree=0.571, adj=0.1, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.571, adj=0.1, (0 split)
## 
## Node number 16380: 27 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.7037037  P(node) =0.00135
##     class counts:     2     8     8     8     1
##    probabilities: 0.074 0.296 0.296 0.296 0.037 
##   left son=32760 (19 obs) right son=32761 (8 obs)
##   Primary splits:
##       age               < 70     to the right, improve=0.9800195, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.9370370, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.8741582, (0 missing)
##       reimbursement2008 < 34375  to the left,  improve=0.5389978, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.3968855, (0 missing)
##   Surrogate splits:
##       cancer < 0.5    to the left,  agree=0.741, adj=0.125, (0 split)
## 
## Node number 16381: 12 observations
##   predicted class=B4  expected loss=0.5  P(node) =0.0006
##     class counts:     2     2     0     6     2
##    probabilities: 0.167 0.167 0.000 0.500 0.167 
## 
## Node number 20570: 70 observations
##   predicted class=B1  expected loss=0.1714286  P(node) =0.0035
##     class counts:    58     7     5     0     0
##    probabilities: 0.829 0.100 0.071 0.000 0.000 
## 
## Node number 20571: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     1     4     2     0     0
##    probabilities: 0.143 0.571 0.286 0.000 0.000 
## 
## Node number 20574: 14 observations
##   predicted class=B1  expected loss=0.1428571  P(node) =0.0007
##     class counts:    12     2     0     0     0
##    probabilities: 0.857 0.143 0.000 0.000 0.000 
## 
## Node number 20575: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     2     5     0     1     0
##    probabilities: 0.250 0.625 0.000 0.125 0.000 
## 
## Node number 23598: 63 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.00315
##     class counts:    45    10     8     0     0
##    probabilities: 0.714 0.159 0.127 0.000 0.000 
## 
## Node number 23599: 56 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.375  P(node) =0.0028
##     class counts:    35    15     3     3     0
##    probabilities: 0.625 0.268 0.054 0.054 0.000 
##   left son=47198 (48 obs) right son=47199 (8 obs)
##   Primary splits:
##       age               < 80.5   to the left,  improve=1.1607140, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.7653061, (0 missing)
##       reimbursement2008 < 1095   to the left,  improve=0.6020408, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.4726553, (0 missing)
##       depression        < 0.5    to the right, improve=0.3311688, (0 missing)
## 
## Node number 24220: 28 observations
##   predicted class=B1  expected loss=0.3214286  P(node) =0.0014
##     class counts:    19     8     1     0     0
##    probabilities: 0.679 0.286 0.036 0.000 0.000 
## 
## Node number 24221: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     3     5     0     0     0
##    probabilities: 0.375 0.625 0.000 0.000 0.000 
## 
## Node number 24222: 65 observations,    complexity param=6.084576e-05
##   predicted class=B1  expected loss=0.3692308  P(node) =0.00325
##     class counts:    41    16     7     0     1
##    probabilities: 0.631 0.246 0.108 0.000 0.015 
##   left son=48444 (58 obs) right son=48445 (7 obs)
##   Primary splits:
##       reimbursement2008 < 1075   to the left,  improve=1.2435770, (0 missing)
##       copd              < 0.5    to the left,  improve=0.9029915, (0 missing)
##       depression        < 0.5    to the right, improve=0.8761474, (0 missing)
##       age               < 55.5   to the left,  improve=0.7910386, (0 missing)
##       kidney            < 0.5    to the right, improve=0.5612040, (0 missing)
## 
## Node number 24223: 14 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.0007
##     class counts:    10     0     4     0     0
##    probabilities: 0.714 0.000 0.286 0.000 0.000 
## 
## Node number 24618: 16 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.0008
##     class counts:    12     2     2     0     0
##    probabilities: 0.750 0.125 0.125 0.000 0.000 
## 
## Node number 24619: 28 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.5  P(node) =0.0014
##     class counts:    14    11     2     0     1
##    probabilities: 0.500 0.393 0.071 0.000 0.036 
##   left son=49238 (20 obs) right son=49239 (8 obs)
##   Primary splits:
##       reimbursement2008 < 1880   to the left,  improve=2.1500000, (0 missing)
##       age               < 50.5   to the right, improve=0.7857143, (0 missing)
## 
## Node number 24674: 29 observations
##   predicted class=B1  expected loss=0.3793103  P(node) =0.00145
##     class counts:    18     9     2     0     0
##    probabilities: 0.621 0.310 0.069 0.000 0.000 
## 
## Node number 24675: 9 observations
##   predicted class=B2  expected loss=0.5555556  P(node) =0.00045
##     class counts:     3     4     2     0     0
##    probabilities: 0.333 0.444 0.222 0.000 0.000 
## 
## Node number 25452: 12 observations
##   predicted class=B1  expected loss=0.4166667  P(node) =0.0006
##     class counts:     7     1     4     0     0
##    probabilities: 0.583 0.083 0.333 0.000 0.000 
## 
## Node number 25453: 24 observations,    complexity param=7.60572e-05
##   predicted class=B1  expected loss=0.625  P(node) =0.0012
##     class counts:     9     9     4     2     0
##    probabilities: 0.375 0.375 0.167 0.083 0.000 
##   left son=50906 (16 obs) right son=50907 (8 obs)
##   Primary splits:
##       age               < 70     to the left,  improve=0.5416667, (0 missing)
##       reimbursement2008 < 2545   to the right, improve=0.3326331, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.2916667, (0 missing)
##       depression        < 0.5    to the right, improve=0.1666667, (0 missing)
##   Surrogate splits:
##       stroke            < 0.5    to the left,  agree=0.75, adj=0.25, (0 split)
##       reimbursement2008 < 2525   to the right, agree=0.75, adj=0.25, (0 split)
## 
## Node number 26680: 7 observations
##   predicted class=B1  expected loss=0.2857143  P(node) =0.00035
##     class counts:     5     1     1     0     0
##    probabilities: 0.714 0.143 0.143 0.000 0.000 
## 
## Node number 26681: 27 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.4814815  P(node) =0.00135
##     class counts:    14    13     0     0     0
##    probabilities: 0.519 0.481 0.000 0.000 0.000 
##   left son=53362 (20 obs) right son=53363 (7 obs)
##   Primary splits:
##       age               < 79.5   to the right, improve=1.02433900, (0 missing)
##       reimbursement2008 < 1950   to the left,  improve=1.02433900, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.05291005, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 2040   to the left,  agree=0.815, adj=0.286, (0 split)
## 
## Node number 26758: 27 observations
##   predicted class=B1  expected loss=0.2962963  P(node) =0.00135
##     class counts:    19     4     3     0     1
##    probabilities: 0.704 0.148 0.111 0.000 0.037 
## 
## Node number 26759: 68 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5588235  P(node) =0.0034
##     class counts:    30    23     8     7     0
##    probabilities: 0.441 0.338 0.118 0.103 0.000 
##   left son=53518 (29 obs) right son=53519 (39 obs)
##   Primary splits:
##       reimbursement2008 < 2145   to the right, improve=1.4809120, (0 missing)
##       age               < 66.5   to the right, improve=1.4399320, (0 missing)
##       copd              < 0.5    to the left,  improve=0.7962224, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.4079739, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.2968627, (0 missing)
##   Surrogate splits:
##       age    < 72.5   to the right, agree=0.603, adj=0.069, (0 split)
##       cancer < 0.5    to the right, agree=0.588, adj=0.034, (0 split)
## 
## Node number 26816: 45 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5111111  P(node) =0.00225
##     class counts:    20    22     2     1     0
##    probabilities: 0.444 0.489 0.044 0.022 0.000 
##   left son=53632 (33 obs) right son=53633 (12 obs)
##   Primary splits:
##       age               < 66.5   to the right, improve=1.1686870, (0 missing)
##       reimbursement2008 < 1605   to the right, improve=0.5349850, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.2204060, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2016637, (0 missing)
##       kidney            < 0.5    to the right, improve=0.1888889, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 1595   to the right, agree=0.778, adj=0.167, (0 split)
## 
## Node number 26817: 10 observations
##   predicted class=B1  expected loss=0.4  P(node) =0.0005
##     class counts:     6     2     0     2     0
##    probabilities: 0.600 0.200 0.000 0.200 0.000 
## 
## Node number 26818: 7 observations
##   predicted class=B2  expected loss=0.1428571  P(node) =0.00035
##     class counts:     1     6     0     0     0
##    probabilities: 0.143 0.857 0.000 0.000 0.000 
## 
## Node number 26819: 26 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.6153846  P(node) =0.0013
##     class counts:     9    10     4     2     1
##    probabilities: 0.346 0.385 0.154 0.077 0.038 
##   left son=53638 (14 obs) right son=53639 (12 obs)
##   Primary splits:
##       reimbursement2008 < 2005   to the right, improve=0.9926740, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.8057692, (0 missing)
##       age               < 67.5   to the right, improve=0.5337995, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.5095571, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3961828, (0 missing)
##   Surrogate splits:
##       diabetes   < 0.5    to the left,  agree=0.692, adj=0.333, (0 split)
##       age        < 66.5   to the right, agree=0.654, adj=0.250, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.577, adj=0.083, (0 split)
##       arthritis  < 0.5    to the left,  agree=0.577, adj=0.083, (0 split)
## 
## Node number 27482: 15 observations
##   predicted class=B1  expected loss=0.4  P(node) =0.00075
##     class counts:     9     5     1     0     0
##    probabilities: 0.600 0.333 0.067 0.000 0.000 
## 
## Node number 27483: 24 observations
##   predicted class=B2  expected loss=0.4166667  P(node) =0.0012
##     class counts:     5    14     5     0     0
##    probabilities: 0.208 0.583 0.208 0.000 0.000 
## 
## Node number 27486: 33 observations
##   predicted class=B2  expected loss=0.3030303  P(node) =0.00165
##     class counts:     4    23     5     1     0
##    probabilities: 0.121 0.697 0.152 0.030 0.000 
## 
## Node number 27487: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     2     2     3     0     0
##    probabilities: 0.286 0.286 0.429 0.000 0.000 
## 
## Node number 27736: 22 observations
##   predicted class=B1  expected loss=0.3636364  P(node) =0.0011
##     class counts:    14     7     1     0     0
##    probabilities: 0.636 0.318 0.045 0.000 0.000 
## 
## Node number 27737: 8 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0004
##     class counts:     2     4     2     0     0
##    probabilities: 0.250 0.500 0.250 0.000 0.000 
## 
## Node number 27750: 20 observations,    complexity param=0.0001014096
##   predicted class=B1  expected loss=0.5  P(node) =0.001
##     class counts:    10     6     2     2     0
##    probabilities: 0.500 0.300 0.100 0.100 0.000 
##   left son=55500 (8 obs) right son=55501 (12 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the right, improve=1.3833330, (0 missing)
##       reimbursement2008 < 3170   to the left,  improve=1.2166670, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5362637, (0 missing)
##       age               < 74.5   to the left,  improve=0.2343434, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.1846154, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 3135   to the left,  agree=0.65, adj=0.125, (0 split)
## 
## Node number 27751: 7 observations
##   predicted class=B3  expected loss=0.5714286  P(node) =0.00035
##     class counts:     1     2     3     0     1
##    probabilities: 0.143 0.286 0.429 0.000 0.143 
## 
## Node number 27754: 12 observations
##   predicted class=B2  expected loss=0.4166667  P(node) =0.0006
##     class counts:     4     7     1     0     0
##    probabilities: 0.333 0.583 0.083 0.000 0.000 
## 
## Node number 27755: 14 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0007
##     class counts:     7     3     3     1     0
##    probabilities: 0.500 0.214 0.214 0.071 0.000 
## 
## Node number 27924: 9 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.00045
##     class counts:     6     2     0     1     0
##    probabilities: 0.667 0.222 0.000 0.111 0.000 
## 
## Node number 27925: 14 observations
##   predicted class=B2  expected loss=0.3571429  P(node) =0.0007
##     class counts:     4     9     1     0     0
##    probabilities: 0.286 0.643 0.071 0.000 0.000 
## 
## Node number 27926: 12 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0006
##     class counts:     8     1     1     2     0
##    probabilities: 0.667 0.083 0.083 0.167 0.000 
## 
## Node number 27927: 9 observations
##   predicted class=B2  expected loss=0.5555556  P(node) =0.00045
##     class counts:     3     4     1     1     0
##    probabilities: 0.333 0.444 0.111 0.111 0.000 
## 
## Node number 28778: 22 observations
##   predicted class=B1  expected loss=0.2727273  P(node) =0.0011
##     class counts:    16     2     4     0     0
##    probabilities: 0.727 0.091 0.182 0.000 0.000 
## 
## Node number 28779: 25 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.52  P(node) =0.00125
##     class counts:    12     4     9     0     0
##    probabilities: 0.480 0.160 0.360 0.000 0.000 
##   left son=57558 (18 obs) right son=57559 (7 obs)
##   Primary splits:
##       reimbursement2008 < 5500   to the left,  improve=1.6933330, (0 missing)
##       age               < 66.5   to the left,  improve=0.3984615, (0 missing)
##       copd              < 0.5    to the left,  improve=0.1516667, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.1238889, (0 missing)
##   Surrogate splits:
##       age < 69.5   to the left,  agree=0.76, adj=0.143, (0 split)
## 
## Node number 30746: 17 observations
##   predicted class=B1  expected loss=0.3529412  P(node) =0.00085
##     class counts:    11     4     2     0     0
##    probabilities: 0.647 0.235 0.118 0.000 0.000 
## 
## Node number 30747: 39 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.6410256  P(node) =0.00195
##     class counts:    14    10    14     1     0
##    probabilities: 0.359 0.256 0.359 0.026 0.000 
##   left son=61494 (16 obs) right son=61495 (23 obs)
##   Primary splits:
##       reimbursement2008 < 4475   to the right, improve=1.2231050, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.7420912, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.5071225, (0 missing)
##       age               < 66.5   to the right, improve=0.4089744, (0 missing)
##       depression        < 0.5    to the left,  improve=0.1756410, (0 missing)
##   Surrogate splits:
##       age < 64     to the right, agree=0.718, adj=0.312, (0 split)
## 
## Node number 30852: 76 observations,    complexity param=0.0003295812
##   predicted class=B1  expected loss=0.4210526  P(node) =0.0038
##     class counts:    44    24     8     0     0
##    probabilities: 0.579 0.316 0.105 0.000 0.000 
##   left son=61704 (48 obs) right son=61705 (28 obs)
##   Primary splits:
##       reimbursement2008 < 8850   to the right, improve=1.9802630, (0 missing)
##       age               < 82.5   to the left,  improve=1.1771250, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.6370279, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.3385965, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.2719298, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=0.961, adj=0.893, (0 split)
##       age        < 74.5   to the right, agree=0.645, adj=0.036, (0 split)
##       ihd        < 0.5    to the right, agree=0.645, adj=0.036, (0 split)
## 
## Node number 30853: 9 observations
##   predicted class=B2  expected loss=0.5555556  P(node) =0.00045
##     class counts:     2     4     2     1     0
##    probabilities: 0.222 0.444 0.222 0.111 0.000 
## 
## Node number 30854: 13 observations
##   predicted class=B1  expected loss=0.5384615  P(node) =0.00065
##     class counts:     6     4     1     2     0
##    probabilities: 0.462 0.308 0.077 0.154 0.000 
## 
## Node number 30855: 8 observations
##   predicted class=B4  expected loss=0.5  P(node) =0.0004
##     class counts:     1     3     0     4     0
##    probabilities: 0.125 0.375 0.000 0.500 0.000 
## 
## Node number 30902: 10 observations
##   predicted class=B2  expected loss=0.3  P(node) =0.0005
##     class counts:     2     7     0     1     0
##    probabilities: 0.200 0.700 0.000 0.100 0.000 
## 
## Node number 30903: 11 observations
##   predicted class=B3  expected loss=0.5454545  P(node) =0.00055
##     class counts:     2     3     5     1     0
##    probabilities: 0.182 0.273 0.455 0.091 0.000 
## 
## Node number 30904: 26 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.5  P(node) =0.0013
##     class counts:    13     7     3     3     0
##    probabilities: 0.500 0.269 0.115 0.115 0.000 
##   left son=61808 (18 obs) right son=61809 (8 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=1.7841880, (0 missing)
##       copd              < 0.5    to the left,  improve=1.6382280, (0 missing)
##       reimbursement2008 < 11300  to the left,  improve=0.6975130, (0 missing)
##       age               < 77.5   to the right, improve=0.5230769, (0 missing)
##       bucket2008        < 3.5    to the left,  improve=0.2302665, (0 missing)
##   Surrogate splits:
##       age < 74.5   to the right, agree=0.769, adj=0.25, (0 split)
## 
## Node number 30905: 12 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0006
##     class counts:     2     6     2     2     0
##    probabilities: 0.167 0.500 0.167 0.167 0.000 
## 
## Node number 31524: 8 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.0004
##     class counts:     6     2     0     0     0
##    probabilities: 0.750 0.250 0.000 0.000 0.000 
## 
## Node number 31525: 24 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0012
##     class counts:     6    12     3     2     1
##    probabilities: 0.250 0.500 0.125 0.083 0.042 
## 
## Node number 31656: 10 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0005
##     class counts:     5     2     1     1     1
##    probabilities: 0.500 0.200 0.100 0.100 0.100 
## 
## Node number 31657: 43 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4651163  P(node) =0.00215
##     class counts:     9    23     6     5     0
##    probabilities: 0.209 0.535 0.140 0.116 0.000 
##   left son=63314 (36 obs) right son=63315 (7 obs)
##   Primary splits:
##       reimbursement2008 < 4140   to the right, improve=1.3715390, (0 missing)
##       age               < 78.5   to the right, improve=0.7748360, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.3783034, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.0576865, (0 missing)
## 
## Node number 31658: 15 observations
##   predicted class=B2  expected loss=0.2666667  P(node) =0.00075
##     class counts:     0    11     3     1     0
##    probabilities: 0.000 0.733 0.200 0.067 0.000 
## 
## Node number 31659: 22 observations
##   predicted class=B3  expected loss=0.5454545  P(node) =0.0011
##     class counts:     4     7    10     1     0
##    probabilities: 0.182 0.318 0.455 0.045 0.000 
## 
## Node number 31660: 10 observations
##   predicted class=B2  expected loss=0.3  P(node) =0.0005
##     class counts:     1     7     2     0     0
##    probabilities: 0.100 0.700 0.200 0.000 0.000 
## 
## Node number 31661: 36 observations,    complexity param=0.0002281716
##   predicted class=B3  expected loss=0.5555556  P(node) =0.0018
##     class counts:     6    12    16     2     0
##    probabilities: 0.167 0.333 0.444 0.056 0.000 
##   left son=63322 (21 obs) right son=63323 (15 obs)
##   Primary splits:
##       reimbursement2008 < 8035   to the right, improve=3.2825400, (0 missing)
##       bucket2008        < 2.5    to the right, improve=3.2825400, (0 missing)
##       cancer            < 0.5    to the right, improve=0.7777778, (0 missing)
##       age               < 68.5   to the left,  improve=0.5569986, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4777778, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the right, agree=1.000, adj=1.000, (0 split)
##       age        < 69.5   to the left,  agree=0.611, adj=0.067, (0 split)
## 
## Node number 31662: 9 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.00045
##     class counts:     6     0     1     1     1
##    probabilities: 0.667 0.000 0.111 0.111 0.111 
## 
## Node number 31663: 19 observations
##   predicted class=B3  expected loss=0.6315789  P(node) =0.00095
##     class counts:     3     6     7     3     0
##    probabilities: 0.158 0.316 0.368 0.158 0.000 
## 
## Node number 31792: 10 observations
##   predicted class=B1  expected loss=0.3  P(node) =0.0005
##     class counts:     7     0     1     1     1
##    probabilities: 0.700 0.000 0.100 0.100 0.100 
## 
## Node number 31793: 14 observations
##   predicted class=B2  expected loss=0.5714286  P(node) =0.0007
##     class counts:     4     6     0     4     0
##    probabilities: 0.286 0.429 0.000 0.286 0.000 
## 
## Node number 31794: 18 observations
##   predicted class=B2  expected loss=0.3888889  P(node) =0.0009
##     class counts:     2    11     4     1     0
##    probabilities: 0.111 0.611 0.222 0.056 0.000 
## 
## Node number 31795: 127 observations,    complexity param=0.0002738059
##   predicted class=B2  expected loss=0.5905512  P(node) =0.00635
##     class counts:    30    52    16    25     4
##    probabilities: 0.236 0.409 0.126 0.197 0.031 
##   left son=63590 (65 obs) right son=63591 (62 obs)
##   Primary splits:
##       age               < 68.5   to the right, improve=1.8156310, (0 missing)
##       reimbursement2008 < 10940  to the left,  improve=1.2503720, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.8431131, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.7185236, (0 missing)
##       depression        < 0.5    to the right, improve=0.7180088, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 9780   to the left,  agree=0.551, adj=0.081, (0 split)
##       depression        < 0.5    to the left,  agree=0.543, adj=0.065, (0 split)
##       cancer            < 0.5    to the left,  agree=0.535, adj=0.048, (0 split)
##       copd              < 0.5    to the left,  agree=0.528, adj=0.032, (0 split)
## 
## Node number 31802: 17 observations
##   predicted class=B1  expected loss=0.5882353  P(node) =0.00085
##     class counts:     7     2     5     2     1
##    probabilities: 0.412 0.118 0.294 0.118 0.059 
## 
## Node number 31803: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     0     1     4     2     0
##    probabilities: 0.000 0.143 0.571 0.286 0.000 
## 
## Node number 31804: 23 observations,    complexity param=7.60572e-05
##   predicted class=B2  expected loss=0.4347826  P(node) =0.00115
##     class counts:     2    13     8     0     0
##    probabilities: 0.087 0.565 0.348 0.000 0.000 
##   left son=63608 (13 obs) right son=63609 (10 obs)
##   Primary splits:
##       reimbursement2008 < 11420  to the left,  improve=0.8956522, (0 missing)
##       copd              < 0.5    to the right, improve=0.8320158, (0 missing)
##       age               < 81.5   to the left,  improve=0.7110368, (0 missing)
##       depression        < 0.5    to the left,  improve=0.3940649, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2033445, (0 missing)
##   Surrogate splits:
##       age    < 80.5   to the left,  agree=0.783, adj=0.5, (0 split)
##       stroke < 0.5    to the left,  agree=0.609, adj=0.1, (0 split)
## 
## Node number 31805: 15 observations
##   predicted class=B2  expected loss=0.5333333  P(node) =0.00075
##     class counts:     1     7     2     5     0
##    probabilities: 0.067 0.467 0.133 0.333 0.000 
## 
## Node number 31840: 12 observations
##   predicted class=B1  expected loss=0.4166667  P(node) =0.0006
##     class counts:     7     2     1     2     0
##    probabilities: 0.583 0.167 0.083 0.167 0.000 
## 
## Node number 31841: 13 observations
##   predicted class=B2  expected loss=0.3846154  P(node) =0.00065
##     class counts:     1     8     2     1     1
##    probabilities: 0.077 0.615 0.154 0.077 0.077 
## 
## Node number 31844: 47 observations,    complexity param=0.0003650745
##   predicted class=B1  expected loss=0.6808511  P(node) =0.00235
##     class counts:    15    14    10     6     2
##    probabilities: 0.319 0.298 0.213 0.128 0.043 
##   left son=63688 (7 obs) right son=63689 (40 obs)
##   Primary splits:
##       age               < 60.5   to the left,  improve=1.8709730, (0 missing)
##       reimbursement2008 < 4015   to the right, improve=1.6709730, (0 missing)
##       depression        < 0.5    to the right, improve=0.9065717, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.6749409, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.3897557, (0 missing)
## 
## Node number 31845: 47 observations
##   predicted class=B2  expected loss=0.4468085  P(node) =0.00235
##     class counts:     7    26     7     7     0
##    probabilities: 0.149 0.553 0.149 0.149 0.000 
## 
## Node number 31846: 39 observations,    complexity param=0.0003650745
##   predicted class=B2  expected loss=0.6923077  P(node) =0.00195
##     class counts:    11    12     9     6     1
##    probabilities: 0.282 0.308 0.231 0.154 0.026 
##   left son=63692 (15 obs) right son=63693 (24 obs)
##   Primary splits:
##       age               < 76.5   to the right, improve=1.3128210, (0 missing)
##       depression        < 0.5    to the right, improve=1.0842490, (0 missing)
##       reimbursement2008 < 5315   to the left,  improve=0.9900135, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.5262614, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.1901824, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 5155   to the left,  agree=0.718, adj=0.267, (0 split)
##       stroke            < 0.5    to the right, agree=0.667, adj=0.133, (0 split)
##       ihd               < 0.5    to the left,  agree=0.641, adj=0.067, (0 split)
## 
## Node number 31847: 29 observations
##   predicted class=B3  expected loss=0.5172414  P(node) =0.00145
##     class counts:     2     6    14     6     1
##    probabilities: 0.069 0.207 0.483 0.207 0.034 
## 
## Node number 32072: 7 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.00035
##     class counts:     4     2     1     0     0
##    probabilities: 0.571 0.286 0.143 0.000 0.000 
## 
## Node number 32073: 15 observations
##   predicted class=B2  expected loss=0.3333333  P(node) =0.00075
##     class counts:     5    10     0     0     0
##    probabilities: 0.333 0.667 0.000 0.000 0.000 
## 
## Node number 32212: 52 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4615385  P(node) =0.0026
##     class counts:     8    28    10     5     1
##    probabilities: 0.154 0.538 0.192 0.096 0.019 
##   left son=64424 (14 obs) right son=64425 (38 obs)
##   Primary splits:
##       reimbursement2008 < 11260  to the left,  improve=2.5399070, (0 missing)
##       alzheimers        < 0.5    to the right, improve=2.0053420, (0 missing)
##       depression        < 0.5    to the right, improve=0.6965171, (0 missing)
##       age               < 75.5   to the left,  improve=0.5668498, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5579070, (0 missing)
##   Surrogate splits:
##       age < 57     to the left,  agree=0.75, adj=0.071, (0 split)
## 
## Node number 32213: 78 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.525641  P(node) =0.0039
##     class counts:     5    37    26     9     1
##    probabilities: 0.064 0.474 0.333 0.115 0.013 
##   left son=64426 (37 obs) right son=64427 (41 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=0.6238358, (0 missing)
##       age               < 79.5   to the left,  improve=0.6101157, (0 missing)
##       reimbursement2008 < 10045  to the right, improve=0.6069777, (0 missing)
##       copd              < 0.5    to the left,  improve=0.3743760, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.3659016, (0 missing)
##   Surrogate splits:
##       age               < 76     to the left,  agree=0.628, adj=0.216, (0 split)
##       reimbursement2008 < 9585   to the right, agree=0.590, adj=0.135, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.564, adj=0.081, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.551, adj=0.054, (0 split)
##       copd              < 0.5    to the left,  agree=0.538, adj=0.027, (0 split)
## 
## Node number 32214: 14 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0007
##     class counts:     0     7     5     0     2
##    probabilities: 0.000 0.500 0.357 0.000 0.143 
## 
## Node number 32215: 8 observations
##   predicted class=B3  expected loss=0.375  P(node) =0.0004
##     class counts:     0     1     5     2     0
##    probabilities: 0.000 0.125 0.625 0.250 0.000 
## 
## Node number 32516: 23 observations
##   predicted class=B1  expected loss=0.4782609  P(node) =0.00115
##     class counts:    12     2     3     6     0
##    probabilities: 0.522 0.087 0.130 0.261 0.000 
## 
## Node number 32517: 18 observations
##   predicted class=B3  expected loss=0.6666667  P(node) =0.0009
##     class counts:     3     5     6     4     0
##    probabilities: 0.167 0.278 0.333 0.222 0.000 
## 
## Node number 32564: 10 observations
##   predicted class=B3  expected loss=0.5  P(node) =0.0005
##     class counts:     2     3     5     0     0
##    probabilities: 0.200 0.300 0.500 0.000 0.000 
## 
## Node number 32565: 29 observations,    complexity param=0.000380286
##   predicted class=B4  expected loss=0.6896552  P(node) =0.00145
##     class counts:     7     8     4     9     1
##    probabilities: 0.241 0.276 0.138 0.310 0.034 
##   left son=65130 (22 obs) right son=65131 (7 obs)
##   Primary splits:
##       age               < 83.5   to the right, improve=1.5293330, (0 missing)
##       reimbursement2008 < 17795  to the right, improve=1.3395230, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.5796935, (0 missing)
##       depression        < 0.5    to the left,  improve=0.5726228, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.4006085, (0 missing)
## 
## Node number 32584: 10 observations
##   predicted class=B2  expected loss=0.6  P(node) =0.0005
##     class counts:     3     4     3     0     0
##    probabilities: 0.300 0.400 0.300 0.000 0.000 
## 
## Node number 32585: 10 observations
##   predicted class=B1  expected loss=0.4  P(node) =0.0005
##     class counts:     6     0     1     3     0
##    probabilities: 0.600 0.000 0.100 0.300 0.000 
## 
## Node number 32590: 10 observations
##   predicted class=B3  expected loss=0.5  P(node) =0.0005
##     class counts:     0     3     5     1     1
##    probabilities: 0.000 0.300 0.500 0.100 0.100 
## 
## Node number 32591: 15 observations
##   predicted class=B4  expected loss=0.6  P(node) =0.00075
##     class counts:     0     5     3     6     1
##    probabilities: 0.000 0.333 0.200 0.400 0.067 
## 
## Node number 32748: 26 observations
##   predicted class=B2  expected loss=0.4615385  P(node) =0.0013
##     class counts:     0    14     3     9     0
##    probabilities: 0.000 0.538 0.115 0.346 0.000 
## 
## Node number 32749: 13 observations
##   predicted class=B4  expected loss=0.3846154  P(node) =0.00065
##     class counts:     0     5     0     8     0
##    probabilities: 0.000 0.385 0.000 0.615 0.000 
## 
## Node number 32752: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     0     5     0     2     0
##    probabilities: 0.000 0.714 0.000 0.286 0.000 
## 
## Node number 32753: 132 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6742424  P(node) =0.0066
##     class counts:    14    43    36    34     5
##    probabilities: 0.106 0.326 0.273 0.258 0.038 
##   left son=65506 (72 obs) right son=65507 (60 obs)
##   Primary splits:
##       age               < 68.5   to the right, improve=1.3924240, (0 missing)
##       reimbursement2008 < 55300  to the right, improve=1.1164590, (0 missing)
##       bucket2008        < 4.5    to the right, improve=1.1164590, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9824242, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.9510963, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 65275  to the left,  agree=0.621, adj=0.167, (0 split)
##       alzheimers        < 0.5    to the left,  agree=0.561, adj=0.033, (0 split)
## 
## Node number 32758: 10 observations
##   predicted class=B3  expected loss=0.5  P(node) =0.0005
##     class counts:     0     1     5     4     0
##    probabilities: 0.000 0.100 0.500 0.400 0.000 
## 
## Node number 32759: 11 observations
##   predicted class=B4  expected loss=0.3636364  P(node) =0.00055
##     class counts:     0     2     2     7     0
##    probabilities: 0.000 0.182 0.182 0.636 0.000 
## 
## Node number 32760: 19 observations
##   predicted class=B3  expected loss=0.6315789  P(node) =0.00095
##     class counts:     2     6     7     4     0
##    probabilities: 0.105 0.316 0.368 0.211 0.000 
## 
## Node number 32761: 8 observations
##   predicted class=B4  expected loss=0.5  P(node) =0.0004
##     class counts:     0     2     1     4     1
##    probabilities: 0.000 0.250 0.125 0.500 0.125 
## 
## Node number 47198: 48 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0024
##     class counts:    32    11     3     2     0
##    probabilities: 0.667 0.229 0.062 0.042 0.000 
##   left son=94396 (38 obs) right son=94397 (10 obs)
##   Primary splits:
##       age               < 74.5   to the left,  improve=0.9486842, (0 missing)
##       reimbursement2008 < 975    to the right, improve=0.4675926, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2881868, (0 missing)
##       depression        < 0.5    to the right, improve=0.1600123, (0 missing)
## 
## Node number 47199: 8 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0004
##     class counts:     3     4     0     1     0
##    probabilities: 0.375 0.500 0.000 0.125 0.000 
## 
## Node number 48444: 58 observations
##   predicted class=B1  expected loss=0.3448276  P(node) =0.0029
##     class counts:    38    12     7     0     1
##    probabilities: 0.655 0.207 0.121 0.000 0.017 
## 
## Node number 48445: 7 observations
##   predicted class=B2  expected loss=0.4285714  P(node) =0.00035
##     class counts:     3     4     0     0     0
##    probabilities: 0.429 0.571 0.000 0.000 0.000 
## 
## Node number 49238: 20 observations
##   predicted class=B1  expected loss=0.35  P(node) =0.001
##     class counts:    13     7     0     0     0
##    probabilities: 0.650 0.350 0.000 0.000 0.000 
## 
## Node number 49239: 8 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0004
##     class counts:     1     4     2     0     1
##    probabilities: 0.125 0.500 0.250 0.000 0.125 
## 
## Node number 50906: 16 observations
##   predicted class=B2  expected loss=0.5625  P(node) =0.0008
##     class counts:     6     7     3     0     0
##    probabilities: 0.375 0.438 0.188 0.000 0.000 
## 
## Node number 50907: 8 observations
##   predicted class=B1  expected loss=0.625  P(node) =0.0004
##     class counts:     3     2     1     2     0
##    probabilities: 0.375 0.250 0.125 0.250 0.000 
## 
## Node number 53362: 20 observations,    complexity param=0.0001216915
##   predicted class=B1  expected loss=0.4  P(node) =0.001
##     class counts:    12     8     0     0     0
##    probabilities: 0.600 0.400 0.000 0.000 0.000 
##   left son=106724 (9 obs) right son=106725 (11 obs)
##   Primary splits:
##       reimbursement2008 < 1790   to the left,  improve=1.0343430, (0 missing)
##       age               < 83.5   to the left,  improve=0.2813187, (0 missing)
##   Surrogate splits:
##       alzheimers < 0.5    to the right, agree=0.65, adj=0.222, (0 split)
##       age        < 81.5   to the right, agree=0.60, adj=0.111, (0 split)
## 
## Node number 53363: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     2     5     0     0     0
##    probabilities: 0.286 0.714 0.000 0.000 0.000 
## 
## Node number 53518: 29 observations,    complexity param=0.0001521144
##   predicted class=B1  expected loss=0.4482759  P(node) =0.00145
##     class counts:    16     7     5     1     0
##    probabilities: 0.552 0.241 0.172 0.034 0.000 
##   left son=107036 (17 obs) right son=107037 (12 obs)
##   Primary splits:
##       age               < 69.5   to the right, improve=1.65483400, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.09270000, (0 missing)
##       reimbursement2008 < 2385   to the left,  improve=0.89789520, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.59811170, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.04075235, (0 missing)
##   Surrogate splits:
##       arthritis         < 0.5    to the left,  agree=0.690, adj=0.250, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.655, adj=0.167, (0 split)
##       reimbursement2008 < 2405   to the left,  agree=0.655, adj=0.167, (0 split)
## 
## Node number 53519: 39 observations,    complexity param=0.0002028192
##   predicted class=B2  expected loss=0.5897436  P(node) =0.00195
##     class counts:    14    16     3     6     0
##    probabilities: 0.359 0.410 0.077 0.154 0.000 
##   left son=107038 (30 obs) right son=107039 (9 obs)
##   Primary splits:
##       reimbursement2008 < 2065   to the left,  improve=1.03418800, (0 missing)
##       age               < 67.5   to the right, improve=0.29641030, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.26290380, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.14529910, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.07020336, (0 missing)
##   Surrogate splits:
##       age < 64.5   to the right, agree=0.795, adj=0.111, (0 split)
## 
## Node number 53632: 33 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.4848485  P(node) =0.00165
##     class counts:    17    14     1     1     0
##    probabilities: 0.515 0.424 0.030 0.030 0.000 
##   left son=107264 (18 obs) right son=107265 (15 obs)
##   Primary splits:
##       reimbursement2008 < 1715   to the left,  improve=0.7535354, (0 missing)
##       age               < 70.5   to the left,  improve=0.5151515, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.1724242, (0 missing)
##       diabetes          < 0.5    to the left,  improve=0.1471861, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.0479798, (0 missing)
##   Surrogate splits:
##       age      < 70.5   to the left,  agree=0.697, adj=0.333, (0 split)
##       diabetes < 0.5    to the left,  agree=0.636, adj=0.200, (0 split)
##       kidney   < 0.5    to the right, agree=0.576, adj=0.067, (0 split)
## 
## Node number 53633: 12 observations
##   predicted class=B2  expected loss=0.3333333  P(node) =0.0006
##     class counts:     3     8     1     0     0
##    probabilities: 0.250 0.667 0.083 0.000 0.000 
## 
## Node number 53638: 14 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0007
##     class counts:     7     5     1     1     0
##    probabilities: 0.500 0.357 0.071 0.071 0.000 
## 
## Node number 53639: 12 observations
##   predicted class=B2  expected loss=0.5833333  P(node) =0.0006
##     class counts:     2     5     3     1     1
##    probabilities: 0.167 0.417 0.250 0.083 0.083 
## 
## Node number 55500: 8 observations
##   predicted class=B1  expected loss=0.25  P(node) =0.0004
##     class counts:     6     1     0     1     0
##    probabilities: 0.750 0.125 0.000 0.125 0.000 
## 
## Node number 55501: 12 observations
##   predicted class=B2  expected loss=0.5833333  P(node) =0.0006
##     class counts:     4     5     2     1     0
##    probabilities: 0.333 0.417 0.167 0.083 0.000 
## 
## Node number 57558: 18 observations
##   predicted class=B1  expected loss=0.3888889  P(node) =0.0009
##     class counts:    11     2     5     0     0
##    probabilities: 0.611 0.111 0.278 0.000 0.000 
## 
## Node number 57559: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     1     2     4     0     0
##    probabilities: 0.143 0.286 0.571 0.000 0.000 
## 
## Node number 61494: 16 observations
##   predicted class=B1  expected loss=0.625  P(node) =0.0008
##     class counts:     6     6     3     1     0
##    probabilities: 0.375 0.375 0.188 0.062 0.000 
## 
## Node number 61495: 23 observations,    complexity param=0.0001521144
##   predicted class=B3  expected loss=0.5217391  P(node) =0.00115
##     class counts:     8     4    11     0     0
##    probabilities: 0.348 0.174 0.478 0.000 0.000 
##   left son=122990 (10 obs) right son=122991 (13 obs)
##   Primary splits:
##       age               < 59     to the left,  improve=0.98394650, (0 missing)
##       reimbursement2008 < 4195   to the right, improve=0.83229810, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.64420290, (0 missing)
##       depression        < 0.5    to the right, improve=0.05452036, (0 missing)
##       ihd               < 0.5    to the left,  improve=0.04420290, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4100   to the right, agree=0.652, adj=0.2, (0 split)
##       heart.failure     < 0.5    to the left,  agree=0.609, adj=0.1, (0 split)
## 
## Node number 61704: 48 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0024
##     class counts:    32    11     5     0     0
##    probabilities: 0.667 0.229 0.104 0.000 0.000 
## 
## Node number 61705: 28 observations,    complexity param=0.0003295812
##   predicted class=B2  expected loss=0.5357143  P(node) =0.0014
##     class counts:    12    13     3     0     0
##    probabilities: 0.429 0.464 0.107 0.000 0.000 
##   left son=123410 (13 obs) right son=123411 (15 obs)
##   Primary splits:
##       reimbursement2008 < 6985   to the left,  improve=4.0794870, (0 missing)
##       copd              < 0.5    to the left,  improve=0.9812834, (0 missing)
##       age               < 80.5   to the left,  improve=0.5000000, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.4692308, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.3750000, (0 missing)
##   Surrogate splits:
##       heart.failure < 0.5    to the left,  agree=0.643, adj=0.231, (0 split)
##       age           < 83     to the right, agree=0.571, adj=0.077, (0 split)
##       bucket2008    < 2.5    to the left,  agree=0.571, adj=0.077, (0 split)
## 
## Node number 61808: 18 observations
##   predicted class=B1  expected loss=0.3888889  P(node) =0.0009
##     class counts:    11     4     0     3     0
##    probabilities: 0.611 0.222 0.000 0.167 0.000 
## 
## Node number 61809: 8 observations
##   predicted class=B2  expected loss=0.625  P(node) =0.0004
##     class counts:     2     3     3     0     0
##    probabilities: 0.250 0.375 0.375 0.000 0.000 
## 
## Node number 63314: 36 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4166667  P(node) =0.0018
##     class counts:     8    21     5     2     0
##    probabilities: 0.222 0.583 0.139 0.056 0.000 
##   left son=126628 (13 obs) right son=126629 (23 obs)
##   Primary splits:
##       reimbursement2008 < 5440   to the left,  improve=1.9760310, (0 missing)
##       age               < 74.5   to the left,  improve=0.7500000, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.5921212, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.1449948, (0 missing)
##   Surrogate splits:
##       age        < 81.5   to the right, agree=0.667, adj=0.077, (0 split)
##       cancer     < 0.5    to the right, agree=0.667, adj=0.077, (0 split)
##       stroke     < 0.5    to the right, agree=0.667, adj=0.077, (0 split)
##       bucket2008 < 2.5    to the left,  agree=0.667, adj=0.077, (0 split)
## 
## Node number 63315: 7 observations
##   predicted class=B4  expected loss=0.5714286  P(node) =0.00035
##     class counts:     1     2     1     3     0
##    probabilities: 0.143 0.286 0.143 0.429 0.000 
## 
## Node number 63322: 21 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5238095  P(node) =0.00105
##     class counts:     4    10     5     2     0
##    probabilities: 0.190 0.476 0.238 0.095 0.000 
##   left son=126644 (9 obs) right son=126645 (12 obs)
##   Primary splits:
##       age               < 67.5   to the left,  improve=1.4841270, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8174603, (0 missing)
##       reimbursement2008 < 11715  to the left,  improve=0.6529304, (0 missing)
##       copd              < 0.5    to the left,  improve=0.4406926, (0 missing)
##       osteoporosis      < 0.5    to the right, improve=0.2619048, (0 missing)
##   Surrogate splits:
##       cancer            < 0.5    to the right, agree=0.714, adj=0.333, (0 split)
##       reimbursement2008 < 10315  to the left,  agree=0.714, adj=0.333, (0 split)
##       osteoporosis      < 0.5    to the right, agree=0.619, adj=0.111, (0 split)
## 
## Node number 63323: 15 observations
##   predicted class=B3  expected loss=0.2666667  P(node) =0.00075
##     class counts:     2     2    11     0     0
##    probabilities: 0.133 0.133 0.733 0.000 0.000 
## 
## Node number 63590: 65 observations,    complexity param=0.0002738059
##   predicted class=B2  expected loss=0.5230769  P(node) =0.00325
##     class counts:    16    31    10     7     1
##    probabilities: 0.246 0.477 0.154 0.108 0.015 
##   left son=127180 (39 obs) right son=127181 (26 obs)
##   Primary splits:
##       reimbursement2008 < 10335  to the left,  improve=2.6871790, (0 missing)
##       age               < 71.5   to the left,  improve=1.7206540, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.6230770, (0 missing)
##       ihd               < 0.5    to the right, improve=1.3879500, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.8410256, (0 missing)
##   Surrogate splits:
##       alzheimers < 0.5    to the left,  agree=0.631, adj=0.077, (0 split)
##       copd       < 0.5    to the left,  agree=0.631, adj=0.077, (0 split)
##       bucket2008 < 2.5    to the left,  agree=0.631, adj=0.077, (0 split)
##       cancer     < 0.5    to the left,  agree=0.615, adj=0.038, (0 split)
## 
## Node number 63591: 62 observations,    complexity param=0.0002738059
##   predicted class=B2  expected loss=0.6612903  P(node) =0.0031
##     class counts:    14    21     6    18     3
##    probabilities: 0.226 0.339 0.097 0.290 0.048 
##   left son=127182 (28 obs) right son=127183 (34 obs)
##   Primary splits:
##       reimbursement2008 < 10290  to the right, improve=1.5262940, (0 missing)
##       age               < 52     to the left,  improve=1.5139440, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.4593000, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9970196, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5110357, (0 missing)
##   Surrogate splits:
##       bucket2008    < 2.5    to the right, agree=0.694, adj=0.321, (0 split)
##       cancer        < 0.5    to the right, agree=0.613, adj=0.143, (0 split)
##       heart.failure < 0.5    to the right, agree=0.597, adj=0.107, (0 split)
##       age           < 64.5   to the right, agree=0.581, adj=0.071, (0 split)
##       copd          < 0.5    to the right, agree=0.581, adj=0.071, (0 split)
## 
## Node number 63608: 13 observations
##   predicted class=B2  expected loss=0.3076923  P(node) =0.00065
##     class counts:     1     9     3     0     0
##    probabilities: 0.077 0.692 0.231 0.000 0.000 
## 
## Node number 63609: 10 observations
##   predicted class=B3  expected loss=0.5  P(node) =0.0005
##     class counts:     1     4     5     0     0
##    probabilities: 0.100 0.400 0.500 0.000 0.000 
## 
## Node number 63688: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     1     5     1     0     0
##    probabilities: 0.143 0.714 0.143 0.000 0.000 
## 
## Node number 63689: 40 observations,    complexity param=0.0003042288
##   predicted class=B1  expected loss=0.65  P(node) =0.002
##     class counts:    14     9     9     6     2
##    probabilities: 0.350 0.225 0.225 0.150 0.050 
##   left son=127378 (14 obs) right son=127379 (26 obs)
##   Primary splits:
##       age               < 71.5   to the left,  improve=1.6214290, (0 missing)
##       reimbursement2008 < 3615   to the right, improve=1.0129630, (0 missing)
##       depression        < 0.5    to the right, improve=0.7313187, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5512788, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.3700000, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 4015   to the right, agree=0.700, adj=0.143, (0 split)
##       osteoporosis      < 0.5    to the right, agree=0.675, adj=0.071, (0 split)
## 
## Node number 63692: 15 observations
##   predicted class=B3  expected loss=0.6  P(node) =0.00075
##     class counts:     4     5     6     0     0
##    probabilities: 0.267 0.333 0.400 0.000 0.000 
## 
## Node number 63693: 24 observations,    complexity param=0.0003650745
##   predicted class=B1  expected loss=0.7083333  P(node) =0.0012
##     class counts:     7     7     3     6     1
##    probabilities: 0.292 0.292 0.125 0.250 0.042 
##   left son=127386 (14 obs) right son=127387 (10 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=1.9714290, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8333333, (0 missing)
##       reimbursement2008 < 5315   to the left,  improve=0.7555556, (0 missing)
##       age               < 67.5   to the right, improve=0.6250000, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5594406, (0 missing)
##   Surrogate splits:
##       age               < 75.5   to the left,  agree=0.708, adj=0.3, (0 split)
##       cancer            < 0.5    to the left,  agree=0.708, adj=0.3, (0 split)
##       reimbursement2008 < 5035   to the right, agree=0.667, adj=0.2, (0 split)
##       copd              < 0.5    to the right, agree=0.625, adj=0.1, (0 split)
## 
## Node number 64424: 14 observations
##   predicted class=B2  expected loss=0.1428571  P(node) =0.0007
##     class counts:     1    12     1     0     0
##    probabilities: 0.071 0.857 0.071 0.000 0.000 
## 
## Node number 64425: 38 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5789474  P(node) =0.0019
##     class counts:     7    16     9     5     1
##    probabilities: 0.184 0.421 0.237 0.132 0.026 
##   left son=128850 (25 obs) right son=128851 (13 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the right, improve=1.7548180, (0 missing)
##       reimbursement2008 < 12915  to the right, improve=1.5553310, (0 missing)
##       copd              < 0.5    to the left,  improve=0.7455870, (0 missing)
##       depression        < 0.5    to the right, improve=0.6704998, (0 missing)
##       age               < 85     to the right, improve=0.5436090, (0 missing)
## 
## Node number 64426: 37 observations
##   predicted class=B2  expected loss=0.4594595  P(node) =0.00185
##     class counts:     3    20    10     4     0
##    probabilities: 0.081 0.541 0.270 0.108 0.000 
## 
## Node number 64427: 41 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5853659  P(node) =0.00205
##     class counts:     2    17    16     5     1
##    probabilities: 0.049 0.415 0.390 0.122 0.024 
##   left son=128854 (34 obs) right son=128855 (7 obs)
##   Primary splits:
##       reimbursement2008 < 10175  to the left,  improve=0.9840131, (0 missing)
##       age               < 64.5   to the left,  improve=0.7571224, (0 missing)
##       stroke            < 0.5    to the right, improve=0.6917388, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.3468219, (0 missing)
##       copd              < 0.5    to the left,  improve=0.2795313, (0 missing)
## 
## Node number 65130: 22 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.6363636  P(node) =0.0011
##     class counts:     6     8     3     5     0
##    probabilities: 0.273 0.364 0.136 0.227 0.000 
##   left son=130260 (10 obs) right son=130261 (12 obs)
##   Primary splits:
##       reimbursement2008 < 17685  to the right, improve=0.7424242, (0 missing)
##       depression        < 0.5    to the left,  improve=0.7305195, (0 missing)
##       age               < 86.5   to the right, improve=0.5415695, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3706294, (0 missing)
##   Surrogate splits:
##       bucket2008 < 3.5    to the right, agree=0.727, adj=0.4, (0 split)
##       age        < 87.5   to the left,  agree=0.591, adj=0.1, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.591, adj=0.1, (0 split)
## 
## Node number 65131: 7 observations
##   predicted class=B4  expected loss=0.4285714  P(node) =0.00035
##     class counts:     1     0     1     4     1
##    probabilities: 0.143 0.000 0.143 0.571 0.143 
## 
## Node number 65506: 72 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6666667  P(node) =0.0036
##     class counts:    11    24    14    20     3
##    probabilities: 0.153 0.333 0.194 0.278 0.042 
##   left son=131012 (65 obs) right son=131013 (7 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the right, improve=1.701282, (0 missing)
##       reimbursement2008 < 55300  to the right, improve=1.679167, (0 missing)
##       bucket2008        < 4.5    to the right, improve=1.679167, (0 missing)
##       age               < 72.5   to the left,  improve=1.502101, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.261148, (0 missing)
## 
## Node number 65507: 60 observations,    complexity param=0.0004563432
##   predicted class=B3  expected loss=0.6333333  P(node) =0.003
##     class counts:     3    19    22    14     2
##    probabilities: 0.050 0.317 0.367 0.233 0.033 
##   left son=131014 (38 obs) right son=131015 (22 obs)
##   Primary splits:
##       osteoporosis      < 0.5    to the left,  improve=1.7395530, (0 missing)
##       reimbursement2008 < 44435  to the left,  improve=1.6555560, (0 missing)
##       alzheimers        < 0.5    to the right, improve=1.1000000, (0 missing)
##       age               < 59.5   to the right, improve=0.5781297, (0 missing)
##       depression        < 0.5    to the left,  improve=0.4219048, (0 missing)
##   Surrogate splits:
##       age < 66.5   to the left,  agree=0.65, adj=0.045, (0 split)
## 
## Node number 94396: 38 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.3684211  P(node) =0.0019
##     class counts:    24    11     2     1     0
##    probabilities: 0.632 0.289 0.053 0.026 0.000 
##   left son=188792 (18 obs) right son=188793 (20 obs)
##   Primary splits:
##       reimbursement2008 < 975    to the right, improve=1.00409400, (0 missing)
##       age               < 71.5   to the left,  improve=0.83583960, (0 missing)
##       depression        < 0.5    to the right, improve=0.22677660, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.07803993, (0 missing)
##   Surrogate splits:
##       age        < 68.5   to the left,  agree=0.658, adj=0.278, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.605, adj=0.167, (0 split)
##       arthritis  < 0.5    to the right, agree=0.553, adj=0.056, (0 split)
##       depression < 0.5    to the right, agree=0.553, adj=0.056, (0 split)
## 
## Node number 94397: 10 observations
##   predicted class=B1  expected loss=0.2  P(node) =0.0005
##     class counts:     8     0     1     1     0
##    probabilities: 0.800 0.000 0.100 0.100 0.000 
## 
## Node number 106724: 9 observations
##   predicted class=B1  expected loss=0.2222222  P(node) =0.00045
##     class counts:     7     2     0     0     0
##    probabilities: 0.778 0.222 0.000 0.000 0.000 
## 
## Node number 106725: 11 observations
##   predicted class=B2  expected loss=0.4545455  P(node) =0.00055
##     class counts:     5     6     0     0     0
##    probabilities: 0.455 0.545 0.000 0.000 0.000 
## 
## Node number 107036: 17 observations
##   predicted class=B1  expected loss=0.2941176  P(node) =0.00085
##     class counts:    12     2     3     0     0
##    probabilities: 0.706 0.118 0.176 0.000 0.000 
## 
## Node number 107037: 12 observations
##   predicted class=B2  expected loss=0.5833333  P(node) =0.0006
##     class counts:     4     5     2     1     0
##    probabilities: 0.333 0.417 0.167 0.083 0.000 
## 
## Node number 107038: 30 observations,    complexity param=0.0002028192
##   predicted class=B1  expected loss=0.5666667  P(node) =0.0015
##     class counts:    13    11     2     4     0
##    probabilities: 0.433 0.367 0.067 0.133 0.000 
##   left son=214076 (12 obs) right son=214077 (18 obs)
##   Primary splits:
##       reimbursement2008 < 1910   to the right, improve=2.00000000, (0 missing)
##       age               < 71.5   to the left,  improve=0.27777780, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.07660455, (0 missing)
##   Surrogate splits:
##       arthritis < 0.5    to the right, agree=0.733, adj=0.333, (0 split)
##       age       < 72.5   to the right, agree=0.667, adj=0.167, (0 split)
##       copd      < 0.5    to the right, agree=0.633, adj=0.083, (0 split)
## 
## Node number 107039: 9 observations
##   predicted class=B2  expected loss=0.4444444  P(node) =0.00045
##     class counts:     1     5     1     2     0
##    probabilities: 0.111 0.556 0.111 0.222 0.000 
## 
## Node number 107264: 18 observations
##   predicted class=B1  expected loss=0.3888889  P(node) =0.0009
##     class counts:    11     6     0     1     0
##    probabilities: 0.611 0.333 0.000 0.056 0.000 
## 
## Node number 107265: 15 observations
##   predicted class=B2  expected loss=0.4666667  P(node) =0.00075
##     class counts:     6     8     1     0     0
##    probabilities: 0.400 0.533 0.067 0.000 0.000 
## 
## Node number 122990: 10 observations
##   predicted class=B1  expected loss=0.5  P(node) =0.0005
##     class counts:     5     2     3     0     0
##    probabilities: 0.500 0.200 0.300 0.000 0.000 
## 
## Node number 122991: 13 observations
##   predicted class=B3  expected loss=0.3846154  P(node) =0.00065
##     class counts:     3     2     8     0     0
##    probabilities: 0.231 0.154 0.615 0.000 0.000 
## 
## Node number 123410: 13 observations
##   predicted class=B1  expected loss=0.3076923  P(node) =0.00065
##     class counts:     9     2     2     0     0
##    probabilities: 0.692 0.154 0.154 0.000 0.000 
## 
## Node number 123411: 15 observations
##   predicted class=B2  expected loss=0.2666667  P(node) =0.00075
##     class counts:     3    11     1     0     0
##    probabilities: 0.200 0.733 0.067 0.000 0.000 
## 
## Node number 126628: 13 observations
##   predicted class=B2  expected loss=0.1538462  P(node) =0.00065
##     class counts:     1    11     1     0     0
##    probabilities: 0.077 0.846 0.077 0.000 0.000 
## 
## Node number 126629: 23 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5652174  P(node) =0.00115
##     class counts:     7    10     4     2     0
##    probabilities: 0.304 0.435 0.174 0.087 0.000 
##   left son=253258 (7 obs) right son=253259 (16 obs)
##   Primary splits:
##       reimbursement2008 < 5980   to the left,  improve=1.2771740, (0 missing)
##       age               < 74.5   to the left,  improve=0.9688406, (0 missing)
##       bucket2008        < 2.5    to the left,  improve=0.5309618, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.2279315, (0 missing)
##   Surrogate splits:
##       bucket2008 < 2.5    to the left,  agree=0.783, adj=0.286, (0 split)
## 
## Node number 126644: 9 observations
##   predicted class=B1  expected loss=0.6666667  P(node) =0.00045
##     class counts:     3     2     3     1     0
##    probabilities: 0.333 0.222 0.333 0.111 0.000 
## 
## Node number 126645: 12 observations
##   predicted class=B2  expected loss=0.3333333  P(node) =0.0006
##     class counts:     1     8     2     1     0
##    probabilities: 0.083 0.667 0.167 0.083 0.000 
## 
## Node number 127180: 39 observations,    complexity param=0.0002738059
##   predicted class=B1  expected loss=0.6410256  P(node) =0.00195
##     class counts:    14    14     7     4     0
##    probabilities: 0.359 0.359 0.179 0.103 0.000 
##   left son=254360 (8 obs) right son=254361 (31 obs)
##   Primary splits:
##       reimbursement2008 < 9355   to the right, improve=2.2578580, (0 missing)
##       age               < 71.5   to the left,  improve=1.1925780, (0 missing)
##       depression        < 0.5    to the right, improve=1.1320510, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.9857550, (0 missing)
##       heart.failure     < 0.5    to the left,  improve=0.8153846, (0 missing)
## 
## Node number 127181: 26 observations
##   predicted class=B2  expected loss=0.3461538  P(node) =0.0013
##     class counts:     2    17     3     3     1
##    probabilities: 0.077 0.654 0.115 0.115 0.038 
## 
## Node number 127182: 28 observations,    complexity param=0.0002738059
##   predicted class=B4  expected loss=0.6428571  P(node) =0.0014
##     class counts:     9     6     2    10     1
##    probabilities: 0.321 0.214 0.071 0.357 0.036 
##   left son=254364 (7 obs) right son=254365 (21 obs)
##   Primary splits:
##       reimbursement2008 < 10940  to the left,  improve=1.880952, (0 missing)
##       age               < 66.5   to the right, improve=1.121429, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.715873, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.515873, (0 missing)
##       depression        < 0.5    to the left,  improve=0.500000, (0 missing)
## 
## Node number 127183: 34 observations,    complexity param=0.0002738059
##   predicted class=B2  expected loss=0.5588235  P(node) =0.0017
##     class counts:     5    15     4     8     2
##    probabilities: 0.147 0.441 0.118 0.235 0.059 
##   left son=254366 (25 obs) right son=254367 (9 obs)
##   Primary splits:
##       age               < 65.5   to the left,  improve=1.9009150, (0 missing)
##       heart.failure     < 0.5    to the right, improve=1.7219250, (0 missing)
##       reimbursement2008 < 8370   to the right, improve=1.2050420, (0 missing)
##       bucket2008        < 2.5    to the right, improve=0.5834881, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5050420, (0 missing)
## 
## Node number 127378: 14 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.0007
##     class counts:     8     3     1     2     0
##    probabilities: 0.571 0.214 0.071 0.143 0.000 
## 
## Node number 127379: 26 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.6923077  P(node) =0.0013
##     class counts:     6     6     8     4     2
##    probabilities: 0.231 0.231 0.308 0.154 0.077 
##   left son=254758 (19 obs) right son=254759 (7 obs)
##   Primary splits:
##       reimbursement2008 < 3885   to the left,  improve=1.2631580, (0 missing)
##       age               < 75.5   to the right, improve=0.8969697, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6388889, (0 missing)
##       heart.failure     < 0.5    to the right, improve=0.4967320, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.4444444, (0 missing)
## 
## Node number 127386: 14 observations
##   predicted class=B2  expected loss=0.5714286  P(node) =0.0007
##     class counts:     5     6     1     1     1
##    probabilities: 0.357 0.429 0.071 0.071 0.071 
## 
## Node number 127387: 10 observations
##   predicted class=B4  expected loss=0.5  P(node) =0.0005
##     class counts:     2     1     2     5     0
##    probabilities: 0.200 0.100 0.200 0.500 0.000 
## 
## Node number 128850: 25 observations
##   predicted class=B2  expected loss=0.48  P(node) =0.00125
##     class counts:     5    13     3     3     1
##    probabilities: 0.200 0.520 0.120 0.120 0.040 
## 
## Node number 128851: 13 observations
##   predicted class=B3  expected loss=0.5384615  P(node) =0.00065
##     class counts:     2     3     6     2     0
##    probabilities: 0.154 0.231 0.462 0.154 0.000 
## 
## Node number 128854: 34 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5294118  P(node) =0.0017
##     class counts:     1    16    12     4     1
##    probabilities: 0.029 0.471 0.353 0.118 0.029 
##   left son=257708 (7 obs) right son=257709 (27 obs)
##   Primary splits:
##       reimbursement2008 < 9480   to the right, improve=0.9333956, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.7647059, (0 missing)
##       copd              < 0.5    to the left,  improve=0.5044172, (0 missing)
##       stroke            < 0.5    to the right, improve=0.4174208, (0 missing)
##       age               < 77.5   to the left,  improve=0.4003268, (0 missing)
## 
## Node number 128855: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     1     1     4     1     0
##    probabilities: 0.143 0.143 0.571 0.143 0.000 
## 
## Node number 130260: 10 observations
##   predicted class=B1  expected loss=0.6  P(node) =0.0005
##     class counts:     4     3     2     1     0
##    probabilities: 0.400 0.300 0.200 0.100 0.000 
## 
## Node number 130261: 12 observations
##   predicted class=B2  expected loss=0.5833333  P(node) =0.0006
##     class counts:     2     5     1     4     0
##    probabilities: 0.167 0.417 0.083 0.333 0.000 
## 
## Node number 131012: 65 observations,    complexity param=0.0004563432
##   predicted class=B2  expected loss=0.6307692  P(node) =0.00325
##     class counts:     9    24    13    16     3
##    probabilities: 0.138 0.369 0.200 0.246 0.046 
##   left son=262024 (46 obs) right son=262025 (19 obs)
##   Primary splits:
##       age               < 72.5   to the right, improve=1.560922, (0 missing)
##       reimbursement2008 < 55990  to the right, improve=1.281022, (0 missing)
##       bucket2008        < 4.5    to the right, improve=1.276687, (0 missing)
##       arthritis         < 0.5    to the left,  improve=1.268239, (0 missing)
##       cancer            < 0.5    to the left,  improve=1.084950, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 69985  to the left,  agree=0.723, adj=0.053, (0 split)
## 
## Node number 131013: 7 observations
##   predicted class=B4  expected loss=0.4285714  P(node) =0.00035
##     class counts:     2     0     1     4     0
##    probabilities: 0.286 0.000 0.143 0.571 0.000 
## 
## Node number 131014: 38 observations,    complexity param=0.0003042288
##   predicted class=B3  expected loss=0.5263158  P(node) =0.0019
##     class counts:     2    10    18     7     1
##    probabilities: 0.053 0.263 0.474 0.184 0.026 
##   left son=262028 (16 obs) right son=262029 (22 obs)
##   Primary splits:
##       reimbursement2008 < 44435  to the left,  improve=1.4210530, (0 missing)
##       depression        < 0.5    to the right, improve=1.1577470, (0 missing)
##       age               < 44     to the left,  improve=0.8219743, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.6702834, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.5996241, (0 missing)
##   Surrogate splits:
##       bucket2008 < 4.5    to the left,  agree=0.789, adj=0.500, (0 split)
##       copd       < 0.5    to the left,  agree=0.737, adj=0.375, (0 split)
##       cancer     < 0.5    to the right, agree=0.658, adj=0.188, (0 split)
##       age        < 49     to the left,  agree=0.632, adj=0.125, (0 split)
## 
## Node number 131015: 22 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.5909091  P(node) =0.0011
##     class counts:     1     9     4     7     1
##    probabilities: 0.045 0.409 0.182 0.318 0.045 
##   left son=262030 (8 obs) right son=262031 (14 obs)
##   Primary splits:
##       depression        < 0.5    to the left,  improve=1.2012990, (0 missing)
##       age               < 61     to the right, improve=0.8966589, (0 missing)
##       reimbursement2008 < 53960  to the right, improve=0.8060606, (0 missing)
##       bucket2008        < 4.5    to the right, improve=0.7272727, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.1060606, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 75515  to the right, agree=0.727, adj=0.250, (0 split)
##       age               < 61     to the right, agree=0.682, adj=0.125, (0 split)
## 
## Node number 188792: 18 observations
##   predicted class=B1  expected loss=0.2222222  P(node) =0.0009
##     class counts:    14     4     0     0     0
##    probabilities: 0.778 0.222 0.000 0.000 0.000 
## 
## Node number 188793: 20 observations,    complexity param=6.519188e-05
##   predicted class=B1  expected loss=0.5  P(node) =0.001
##     class counts:    10     7     2     1     0
##    probabilities: 0.500 0.350 0.100 0.050 0.000 
##   left son=377586 (12 obs) right son=377587 (8 obs)
##   Primary splits:
##       age               < 71.5   to the left,  improve=1.883333, (0 missing)
##       reimbursement2008 < 915    to the left,  improve=1.451515, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.256044, (0 missing)
##   Surrogate splits:
##       arthritis         < 0.5    to the left,  agree=0.7, adj=0.25, (0 split)
##       reimbursement2008 < 930    to the left,  agree=0.7, adj=0.25, (0 split)
## 
## Node number 214076: 12 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0006
##     class counts:     8     2     0     2     0
##    probabilities: 0.667 0.167 0.000 0.167 0.000 
## 
## Node number 214077: 18 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0009
##     class counts:     5     9     2     2     0
##    probabilities: 0.278 0.500 0.111 0.111 0.000 
## 
## Node number 253258: 7 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.00035
##     class counts:     4     2     0     1     0
##    probabilities: 0.571 0.286 0.000 0.143 0.000 
## 
## Node number 253259: 16 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0008
##     class counts:     3     8     4     1     0
##    probabilities: 0.188 0.500 0.250 0.062 0.000 
## 
## Node number 254360: 8 observations
##   predicted class=B1  expected loss=0.375  P(node) =0.0004
##     class counts:     5     0     1     2     0
##    probabilities: 0.625 0.000 0.125 0.250 0.000 
## 
## Node number 254361: 31 observations,    complexity param=0.0002738059
##   predicted class=B2  expected loss=0.5483871  P(node) =0.00155
##     class counts:     9    14     6     2     0
##    probabilities: 0.290 0.452 0.194 0.065 0.000 
##   left son=508722 (9 obs) right son=508723 (22 obs)
##   Primary splits:
##       heart.failure     < 0.5    to the left,  improve=1.6226780, (0 missing)
##       age               < 71.5   to the left,  improve=1.3876390, (0 missing)
##       reimbursement2008 < 7390   to the right, improve=0.9646697, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.8980031, (0 missing)
##       copd              < 0.5    to the right, improve=0.8980031, (0 missing)
## 
## Node number 254364: 7 observations
##   predicted class=B1  expected loss=0.4285714  P(node) =0.00035
##     class counts:     4     0     2     1     0
##    probabilities: 0.571 0.000 0.286 0.143 0.000 
## 
## Node number 254365: 21 observations,    complexity param=0.0001521144
##   predicted class=B4  expected loss=0.5714286  P(node) =0.00105
##     class counts:     5     6     0     9     1
##    probabilities: 0.238 0.286 0.000 0.429 0.048 
##   left son=508730 (13 obs) right son=508731 (8 obs)
##   Primary splits:
##       alzheimers        < 0.5    to the left,  improve=0.8635531, (0 missing)
##       depression        < 0.5    to the left,  improve=0.6995671, (0 missing)
##       age               < 65.5   to the right, improve=0.5943223, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.3571429, (0 missing)
##       reimbursement2008 < 12015  to the right, improve=0.3250916, (0 missing)
##   Surrogate splits:
##       copd              < 0.5    to the left,  agree=0.762, adj=0.375, (0 split)
##       age               < 49     to the right, agree=0.714, adj=0.250, (0 split)
##       reimbursement2008 < 14250  to the left,  agree=0.714, adj=0.250, (0 split)
##       cancer            < 0.5    to the left,  agree=0.667, adj=0.125, (0 split)
## 
## Node number 254366: 25 observations
##   predicted class=B2  expected loss=0.48  P(node) =0.00125
##     class counts:     4    13     3     3     2
##    probabilities: 0.160 0.520 0.120 0.120 0.080 
## 
## Node number 254367: 9 observations
##   predicted class=B4  expected loss=0.4444444  P(node) =0.00045
##     class counts:     1     2     1     5     0
##    probabilities: 0.111 0.222 0.111 0.556 0.000 
## 
## Node number 254758: 19 observations
##   predicted class=B1  expected loss=0.6842105  P(node) =0.00095
##     class counts:     6     4     4     3     2
##    probabilities: 0.316 0.211 0.211 0.158 0.105 
## 
## Node number 254759: 7 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.00035
##     class counts:     0     2     4     1     0
##    probabilities: 0.000 0.286 0.571 0.143 0.000 
## 
## Node number 257708: 7 observations
##   predicted class=B2  expected loss=0.2857143  P(node) =0.00035
##     class counts:     0     5     1     1     0
##    probabilities: 0.000 0.714 0.143 0.143 0.000 
## 
## Node number 257709: 27 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5925926  P(node) =0.00135
##     class counts:     1    11    11     3     1
##    probabilities: 0.037 0.407 0.407 0.111 0.037 
##   left son=515418 (19 obs) right son=515419 (8 obs)
##   Primary splits:
##       reimbursement2008 < 9020   to the left,  improve=1.7875240, (0 missing)
##       age               < 70.5   to the left,  improve=0.8518519, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.8274318, (0 missing)
##       stroke            < 0.5    to the right, improve=0.4010582, (0 missing)
##       alzheimers        < 0.5    to the left,  improve=0.3909933, (0 missing)
## 
## Node number 262024: 46 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.5869565  P(node) =0.0023
##     class counts:     5    19    11     8     3
##    probabilities: 0.109 0.413 0.239 0.174 0.065 
##   left son=524048 (25 obs) right son=524049 (21 obs)
##   Primary splits:
##       reimbursement2008 < 52775  to the right, improve=1.6160660, (0 missing)
##       depression        < 0.5    to the right, improve=1.0500350, (0 missing)
##       bucket2008        < 4.5    to the right, improve=1.0446380, (0 missing)
##       cancer            < 0.5    to the left,  improve=0.9895186, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.8413043, (0 missing)
##   Surrogate splits:
##       bucket2008 < 4.5    to the right, agree=0.913, adj=0.810, (0 split)
##       arthritis  < 0.5    to the left,  agree=0.630, adj=0.190, (0 split)
##       depression < 0.5    to the right, agree=0.630, adj=0.190, (0 split)
##       cancer     < 0.5    to the left,  agree=0.587, adj=0.095, (0 split)
##       copd       < 0.5    to the right, agree=0.587, adj=0.095, (0 split)
## 
## Node number 262025: 19 observations
##   predicted class=B4  expected loss=0.5789474  P(node) =0.00095
##     class counts:     4     5     2     8     0
##    probabilities: 0.211 0.263 0.105 0.421 0.000 
## 
## Node number 262028: 16 observations
##   predicted class=B3  expected loss=0.375  P(node) =0.0008
##     class counts:     2     2    10     2     0
##    probabilities: 0.125 0.125 0.625 0.125 0.000 
## 
## Node number 262029: 22 observations,    complexity param=0.0003042288
##   predicted class=B2  expected loss=0.6363636  P(node) =0.0011
##     class counts:     0     8     8     5     1
##    probabilities: 0.000 0.364 0.364 0.227 0.045 
##   left son=524058 (12 obs) right son=524059 (10 obs)
##   Primary splits:
##       depression        < 0.5    to the right, improve=1.5666670, (0 missing)
##       reimbursement2008 < 66505  to the right, improve=1.0000000, (0 missing)
##       age               < 58.5   to the left,  improve=0.9642857, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.6761905, (0 missing)
##       arthritis         < 0.5    to the right, improve=0.4358974, (0 missing)
##   Surrogate splits:
##       reimbursement2008 < 67825  to the left,  agree=0.773, adj=0.5, (0 split)
##       age               < 66.5   to the left,  agree=0.682, adj=0.3, (0 split)
##       alzheimers        < 0.5    to the right, agree=0.682, adj=0.3, (0 split)
##       arthritis         < 0.5    to the right, agree=0.591, adj=0.1, (0 split)
##       copd              < 0.5    to the right, agree=0.591, adj=0.1, (0 split)
## 
## Node number 262030: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     1     5     1     1     0
##    probabilities: 0.125 0.625 0.125 0.125 0.000 
## 
## Node number 262031: 14 observations
##   predicted class=B4  expected loss=0.5714286  P(node) =0.0007
##     class counts:     0     4     3     6     1
##    probabilities: 0.000 0.286 0.214 0.429 0.071 
## 
## Node number 377586: 12 observations
##   predicted class=B1  expected loss=0.3333333  P(node) =0.0006
##     class counts:     8     2     1     1     0
##    probabilities: 0.667 0.167 0.083 0.083 0.000 
## 
## Node number 377587: 8 observations
##   predicted class=B2  expected loss=0.375  P(node) =0.0004
##     class counts:     2     5     1     0     0
##    probabilities: 0.250 0.625 0.125 0.000 0.000 
## 
## Node number 508722: 9 observations
##   predicted class=B1  expected loss=0.4444444  P(node) =0.00045
##     class counts:     5     2     2     0     0
##    probabilities: 0.556 0.222 0.222 0.000 0.000 
## 
## Node number 508723: 22 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.4545455  P(node) =0.0011
##     class counts:     4    12     4     2     0
##    probabilities: 0.182 0.545 0.182 0.091 0.000 
##   left son=1017446 (12 obs) right son=1017447 (10 obs)
##   Primary splits:
##       age               < 71.5   to the left,  improve=1.9848480, (0 missing)
##       reimbursement2008 < 7425   to the right, improve=1.2086580, (0 missing)
##       depression        < 0.5    to the right, improve=1.1002330, (0 missing)
##       copd              < 0.5    to the right, improve=0.9967532, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.6753247, (0 missing)
##   Surrogate splits:
##       depression        < 0.5    to the right, agree=0.682, adj=0.3, (0 split)
##       copd              < 0.5    to the right, agree=0.636, adj=0.2, (0 split)
##       ihd               < 0.5    to the right, agree=0.636, adj=0.2, (0 split)
##       osteoporosis      < 0.5    to the left,  agree=0.636, adj=0.2, (0 split)
##       reimbursement2008 < 7010   to the right, agree=0.636, adj=0.2, (0 split)
## 
## Node number 508730: 13 observations
##   predicted class=B2  expected loss=0.6153846  P(node) =0.00065
##     class counts:     3     5     0     4     1
##    probabilities: 0.231 0.385 0.000 0.308 0.077 
## 
## Node number 508731: 8 observations
##   predicted class=B4  expected loss=0.375  P(node) =0.0004
##     class counts:     2     1     0     5     0
##    probabilities: 0.250 0.125 0.000 0.625 0.000 
## 
## Node number 515418: 19 observations
##   predicted class=B2  expected loss=0.5263158  P(node) =0.00095
##     class counts:     1     9     5     3     1
##    probabilities: 0.053 0.474 0.263 0.158 0.053 
## 
## Node number 515419: 8 observations
##   predicted class=B3  expected loss=0.25  P(node) =0.0004
##     class counts:     0     2     6     0     0
##    probabilities: 0.000 0.250 0.750 0.000 0.000 
## 
## Node number 524048: 25 observations,    complexity param=0.0002281716
##   predicted class=B2  expected loss=0.64  P(node) =0.00125
##     class counts:     4     9     9     2     1
##    probabilities: 0.160 0.360 0.360 0.080 0.040 
##   left son=1048096 (11 obs) right son=1048097 (14 obs)
##   Primary splits:
##       reimbursement2008 < 59785  to the right, improve=2.4722080, (0 missing)
##       age               < 76.5   to the right, improve=0.7825641, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.5466667, (0 missing)
##       osteoporosis      < 0.5    to the left,  improve=0.2682353, (0 missing)
##       depression        < 0.5    to the right, improve=0.1561905, (0 missing)
##   Surrogate splits:
##       age        < 79.5   to the right, agree=0.64, adj=0.182, (0 split)
##       alzheimers < 0.5    to the left,  agree=0.64, adj=0.182, (0 split)
##       cancer     < 0.5    to the right, agree=0.64, adj=0.182, (0 split)
##       depression < 0.5    to the left,  agree=0.60, adj=0.091, (0 split)
##       bucket2008 < 4.5    to the right, agree=0.60, adj=0.091, (0 split)
## 
## Node number 524049: 21 observations,    complexity param=0.0001521144
##   predicted class=B2  expected loss=0.5238095  P(node) =0.00105
##     class counts:     1    10     2     6     2
##    probabilities: 0.048 0.476 0.095 0.286 0.095 
##   left son=1048098 (7 obs) right son=1048099 (14 obs)
##   Primary splits:
##       copd              < 0.5    to the left,  improve=1.9523810, (0 missing)
##       depression        < 0.5    to the left,  improve=1.1316020, (0 missing)
##       reimbursement2008 < 41140  to the left,  improve=1.0760070, (0 missing)
##       arthritis         < 0.5    to the left,  improve=0.4043290, (0 missing)
##       alzheimers        < 0.5    to the right, improve=0.2875458, (0 missing)
##   Surrogate splits:
##       age               < 78.5   to the right, agree=0.810, adj=0.429, (0 split)
##       reimbursement2008 < 40060  to the left,  agree=0.762, adj=0.286, (0 split)
## 
## Node number 524058: 12 observations
##   predicted class=B2  expected loss=0.5  P(node) =0.0006
##     class counts:     0     6     2     3     1
##    probabilities: 0.000 0.500 0.167 0.250 0.083 
## 
## Node number 524059: 10 observations
##   predicted class=B3  expected loss=0.4  P(node) =0.0005
##     class counts:     0     2     6     2     0
##    probabilities: 0.000 0.200 0.600 0.200 0.000 
## 
## Node number 1017446: 12 observations
##   predicted class=B2  expected loss=0.25  P(node) =0.0006
##     class counts:     2     9     0     1     0
##    probabilities: 0.167 0.750 0.000 0.083 0.000 
## 
## Node number 1017447: 10 observations
##   predicted class=B3  expected loss=0.6  P(node) =0.0005
##     class counts:     2     3     4     1     0
##    probabilities: 0.200 0.300 0.400 0.100 0.000 
## 
## Node number 1048096: 11 observations
##   predicted class=B1  expected loss=0.6363636  P(node) =0.00055
##     class counts:     4     4     1     2     0
##    probabilities: 0.364 0.364 0.091 0.182 0.000 
## 
## Node number 1048097: 14 observations
##   predicted class=B3  expected loss=0.4285714  P(node) =0.0007
##     class counts:     0     5     8     0     1
##    probabilities: 0.000 0.357 0.571 0.000 0.071 
## 
## Node number 1048098: 7 observations
##   predicted class=B2  expected loss=0.1428571  P(node) =0.00035
##     class counts:     0     6     0     1     0
##    probabilities: 0.000 0.857 0.000 0.143 0.000 
## 
## Node number 1048099: 14 observations
##   predicted class=B4  expected loss=0.6428571  P(node) =0.0007
##     class counts:     1     4     2     5     2
##    probabilities: 0.071 0.286 0.143 0.357 0.143 
## 
## n= 20000 
## 
## node), split, n, loss, yval, (yprob)
##       * denotes terminal node
## 
##       1) root 20000 6574 B1 (0.67 0.19 0.089 0.043 0.0057)  
##         2) reimbursement2008< 1565 12142 1549 B1 (0.87 0.077 0.036 0.014 0.0016)  
##           4) reimbursement2008< 195 6456  205 B1 (0.97 0.017 0.011 0.0039 0.00046) *
##           5) reimbursement2008>=195 5686 1344 B1 (0.76 0.15 0.064 0.024 0.0028)  
##            10) reimbursement2008< 685 2374  402 B1 (0.83 0.1 0.052 0.015 0.0021)  
##              20) diabetes< 0.5 1860  289 B1 (0.84 0.095 0.046 0.012 0.0022)  
##                40) age< 89.5 1774  266 B1 (0.85 0.093 0.042 0.013 0.0017)  
##                  80) age>=29.5 1764  262 B1 (0.85 0.092 0.043 0.012 0.0017)  
##                   160) osteoporosis< 0.5 1586  227 B1 (0.86 0.086 0.043 0.012 0.0019)  
##                     320) age< 71.5 756   92 B1 (0.88 0.075 0.036 0.0093 0.0013) *
##                     321) age>=71.5 830  135 B1 (0.84 0.096 0.049 0.014 0.0024)  
##                       642) reimbursement2008< 665 801  127 B1 (0.84 0.091 0.05 0.015 0.0025)  
##                        1284) reimbursement2008< 245 94   10 B1 (0.89 0.053 0.043 0.011 0) *
##                        1285) reimbursement2008>=245 707  117 B1 (0.83 0.096 0.051 0.016 0.0028)  
##                          2570) reimbursement2008>=495 277   38 B1 (0.86 0.076 0.036 0.025 0) *
##                          2571) reimbursement2008< 495 430   79 B1 (0.82 0.11 0.06 0.0093 0.0047)  
##                            5142) reimbursement2008< 475 398   70 B1 (0.82 0.098 0.065 0.0075 0.005)  
##                             10284) ihd< 0.5 321   52 B1 (0.84 0.087 0.059 0.0093 0.0062) *
##                             10285) ihd>=0.5 77   18 B1 (0.77 0.14 0.091 0 0)  
##                               20570) age< 86.5 70   12 B1 (0.83 0.1 0.071 0 0) *
##                               20571) age>=86.5 7    3 B2 (0.14 0.57 0.29 0 0) *
##                            5143) reimbursement2008>=475 32    9 B1 (0.72 0.25 0 0.031 0)  
##                             10286) age>=83.5 10    1 B1 (0.9 0.1 0 0 0) *
##                             10287) age< 83.5 22    8 B1 (0.64 0.32 0 0.045 0)  
##                               20574) age< 78.5 14    2 B1 (0.86 0.14 0 0 0) *
##                               20575) age>=78.5 8    3 B2 (0.25 0.62 0 0.12 0) *
##                       643) reimbursement2008>=665 29    8 B1 (0.72 0.24 0.034 0 0) *
##                   161) osteoporosis>=0.5 178   35 B1 (0.8 0.14 0.039 0.017 0)  
##                     322) reimbursement2008>=225 171   31 B1 (0.82 0.12 0.041 0.018 0) *
##                     323) reimbursement2008< 225 7    3 B2 (0.43 0.57 0 0 0) *
##                  81) age< 29.5 10    4 B1 (0.6 0.3 0 0.1 0) *
##                41) age>=89.5 86   23 B1 (0.73 0.13 0.13 0 0.012) *
##              21) diabetes>=0.5 514  113 B1 (0.78 0.12 0.072 0.023 0.0019)  
##                42) reimbursement2008< 425 173   28 B1 (0.84 0.075 0.064 0.023 0)  
##                  84) age>=64.5 147   18 B1 (0.88 0.061 0.048 0.014 0) *
##                  85) age< 64.5 26   10 B1 (0.62 0.15 0.15 0.077 0)  
##                   170) reimbursement2008>=250 19    5 B1 (0.74 0.11 0.053 0.11 0) *
##                   171) reimbursement2008< 250 7    4 B3 (0.29 0.29 0.43 0 0) *
##                43) reimbursement2008>=425 341   85 B1 (0.75 0.15 0.076 0.023 0.0029) *
##            11) reimbursement2008>=685 3312  942 B1 (0.72 0.18 0.073 0.031 0.0033)  
##              22) ihd< 0.5 1722  424 B1 (0.75 0.15 0.062 0.03 0.0029)  
##                44) reimbursement2008< 1085 951  209 B1 (0.78 0.14 0.05 0.027 0.0032)  
##                  88) alzheimers< 0.5 811  169 B1 (0.79 0.13 0.047 0.03 0.0025)  
##                   176) diabetes< 0.5 544  105 B1 (0.81 0.11 0.048 0.031 0.0037)  
##                     352) reimbursement2008< 905 338   59 B1 (0.83 0.086 0.059 0.024 0.0059) *
##                     353) reimbursement2008>=905 206   46 B1 (0.78 0.15 0.029 0.044 0)  
##                       706) reimbursement2008>=955 149   25 B1 (0.83 0.12 0.02 0.027 0) *
##                       707) reimbursement2008< 955 57   21 B1 (0.63 0.23 0.053 0.088 0)  
##                        1414) age< 83.5 43   12 B1 (0.72 0.14 0.07 0.07 0) *
##                        1415) age>=83.5 14    7 B2 (0.36 0.5 0 0.14 0) *
##                   177) diabetes>=0.5 267   64 B1 (0.76 0.17 0.045 0.026 0)  
##                     354) reimbursement2008>=795 182   38 B1 (0.79 0.13 0.049 0.027 0) *
##                     355) reimbursement2008< 795 85   26 B1 (0.69 0.25 0.035 0.024 0)  
##                       710) reimbursement2008< 785 76   21 B1 (0.72 0.21 0.039 0.026 0)  
##                        1420) age>=81 9    1 B1 (0.89 0 0 0.11 0) *
##                        1421) age< 81 67   20 B1 (0.7 0.24 0.045 0.015 0)  
##                          2842) age< 78.5 60   16 B1 (0.73 0.2 0.05 0.017 0) *
##                          2843) age>=78.5 7    3 B2 (0.43 0.57 0 0 0) *
##                       711) reimbursement2008>=785 9    4 B2 (0.44 0.56 0 0 0) *
##                  89) alzheimers>=0.5 140   40 B1 (0.71 0.19 0.071 0.014 0.0071)  
##                   178) age< 91.5 133   35 B1 (0.74 0.18 0.068 0.0075 0.0075) *
##                   179) age>=91.5 7    4 B2 (0.29 0.43 0.14 0.14 0) *
##                45) reimbursement2008>=1085 771  215 B1 (0.72 0.17 0.077 0.032 0.0026)  
##                  90) stroke< 0.5 758  207 B1 (0.73 0.17 0.071 0.033 0.0026)  
##                   180) osteoporosis< 0.5 586  150 B1 (0.74 0.15 0.073 0.032 0)  
##                     360) age>=67.5 449  107 B1 (0.76 0.13 0.08 0.031 0)  
##                       720) reimbursement2008< 1335 283   60 B1 (0.79 0.1 0.078 0.032 0)  
##                        1440) age>=87.5 27    2 B1 (0.93 0.037 0.037 0 0) *
##                        1441) age< 87.5 256   58 B1 (0.77 0.11 0.082 0.035 0)  
##                          2882) age< 80.5 197   38 B1 (0.81 0.091 0.066 0.036 0) *
##                          2883) age>=80.5 59   20 B1 (0.66 0.17 0.14 0.034 0)  
##                            5766) reimbursement2008>=1115 51   15 B1 (0.71 0.12 0.14 0.039 0) *
##                            5767) reimbursement2008< 1115 8    4 B2 (0.38 0.5 0.12 0 0) *
##                       721) reimbursement2008>=1335 166   47 B1 (0.72 0.17 0.084 0.03 0)  
##                        1442) copd< 0.5 158   43 B1 (0.73 0.16 0.082 0.032 0)  
##                          2884) age>=73.5 109   31 B1 (0.72 0.19 0.083 0.0092 0)  
##                            5768) age>=77.5 79   18 B1 (0.77 0.14 0.076 0.013 0) *
##                            5769) age< 77.5 30   13 B1 (0.57 0.33 0.1 0 0)  
##                             11538) arthritis< 0.5 23    8 B1 (0.65 0.22 0.13 0 0) *
##                             11539) arthritis>=0.5 7    2 B2 (0.29 0.71 0 0 0) *
##                          2885) age< 73.5 49   12 B1 (0.76 0.082 0.082 0.082 0) *
##                        1443) copd>=0.5 8    4 B1 (0.5 0.38 0.12 0 0) *
##                     361) age< 67.5 137   43 B1 (0.69 0.23 0.051 0.036 0)  
##                       722) reimbursement2008>=1345 50   13 B1 (0.74 0.14 0.08 0.04 0) *
##                       723) reimbursement2008< 1345 87   30 B1 (0.66 0.28 0.034 0.034 0)  
##                        1446) reimbursement2008< 1235 52   15 B1 (0.71 0.19 0.038 0.058 0)  
##                          2892) reimbursement2008>=1155 32    6 B1 (0.81 0.12 0.031 0.031 0) *
##                          2893) reimbursement2008< 1155 20    9 B1 (0.55 0.3 0.05 0.1 0)  
##                            5786) reimbursement2008< 1115 9    2 B1 (0.78 0.11 0 0.11 0) *
##                            5787) reimbursement2008>=1115 11    6 B2 (0.36 0.45 0.091 0.091 0) *
##                        1447) reimbursement2008>=1235 35   15 B1 (0.57 0.4 0.029 0 0)  
##                          2894) diabetes>=0.5 15    4 B1 (0.73 0.2 0.067 0 0) *
##                          2895) diabetes< 0.5 20    9 B2 (0.45 0.55 0 0 0)  
##                            5790) reimbursement2008>=1275 11    5 B1 (0.55 0.45 0 0 0) *
##                            5791) reimbursement2008< 1275 9    3 B2 (0.33 0.67 0 0 0) *
##                   181) osteoporosis>=0.5 172   57 B1 (0.67 0.22 0.064 0.035 0.012)  
##                     362) age< 83.5 143   42 B1 (0.71 0.2 0.056 0.028 0.014)  
##                       724) age>=75.5 44    8 B1 (0.82 0.11 0.023 0.023 0.023) *
##                       725) age< 75.5 99   34 B1 (0.66 0.23 0.071 0.03 0.01)  
##                        1450) age< 73.5 88   26 B1 (0.7 0.19 0.057 0.034 0.011) *
##                        1451) age>=73.5 11    5 B2 (0.27 0.55 0.18 0 0) *
##                     363) age>=83.5 29   15 B1 (0.48 0.34 0.1 0.069 0)  
##                       726) diabetes< 0.5 17    6 B1 (0.65 0.24 0.059 0.059 0) *
##                       727) diabetes>=0.5 12    6 B2 (0.25 0.5 0.17 0.083 0) *
##                  91) stroke>=0.5 13    8 B1 (0.38 0.23 0.38 0 0) *
##              23) ihd>=0.5 1590  518 B1 (0.67 0.2 0.084 0.033 0.0038)  
##                46) diabetes< 0.5 771  220 B1 (0.71 0.18 0.078 0.022 0.0052)  
##                  92) kidney< 0.5 713  194 B1 (0.73 0.18 0.072 0.02 0.0056)  
##                   184) age>=39.5 691  184 B1 (0.73 0.17 0.072 0.019 0.0029)  
##                     368) reimbursement2008< 1465 628  161 B1 (0.74 0.17 0.068 0.019 0.0032)  
##                       736) heart.failure< 0.5 455  105 B1 (0.77 0.15 0.057 0.015 0.0044) *
##                       737) heart.failure>=0.5 173   56 B1 (0.68 0.2 0.098 0.029 0)  
##                        1474) reimbursement2008>=820 145   41 B1 (0.72 0.17 0.09 0.021 0)  
##                          2948) age< 51 8    0 B1 (1 0 0 0 0) *
##                          2949) age>=51 137   41 B1 (0.7 0.18 0.095 0.022 0)  
##                            5898) copd>=0.5 10    1 B1 (0.9 0 0.1 0 0) *
##                            5899) copd< 0.5 127   40 B1 (0.69 0.2 0.094 0.024 0)  
##                             11798) reimbursement2008< 875 8    1 B1 (0.88 0 0.12 0 0) *
##                             11799) reimbursement2008>=875 119   39 B1 (0.67 0.21 0.092 0.025 0)  
##                               23598) reimbursement2008>=1125 63   18 B1 (0.71 0.16 0.13 0 0) *
##                               23599) reimbursement2008< 1125 56   21 B1 (0.62 0.27 0.054 0.054 0)  
##                                 47198) age< 80.5 48   16 B1 (0.67 0.23 0.062 0.042 0)  
##                                   94396) age< 74.5 38   14 B1 (0.63 0.29 0.053 0.026 0)  
##                                    188792) reimbursement2008>=975 18    4 B1 (0.78 0.22 0 0 0) *
##                                    188793) reimbursement2008< 975 20   10 B1 (0.5 0.35 0.1 0.05 0)  
##                                      377586) age< 71.5 12    4 B1 (0.67 0.17 0.083 0.083 0) *
##                                      377587) age>=71.5 8    3 B2 (0.25 0.62 0.12 0 0) *
##                                   94397) age>=74.5 10    2 B1 (0.8 0 0.1 0.1 0) *
##                                 47199) age>=80.5 8    4 B2 (0.38 0.5 0 0.12 0) *
##                        1475) reimbursement2008< 820 28   15 B1 (0.46 0.32 0.14 0.071 0)  
##                          2950) age>=78.5 8    2 B1 (0.75 0.12 0 0.12 0) *
##                          2951) age< 78.5 20   12 B2 (0.35 0.4 0.2 0.05 0)  
##                            5902) age< 66.5 7    4 B1 (0.43 0.29 0.29 0 0) *
##                            5903) age>=66.5 13    7 B2 (0.31 0.46 0.15 0.077 0) *
##                     369) reimbursement2008>=1465 63   23 B1 (0.63 0.24 0.11 0.016 0)  
##                       738) reimbursement2008>=1485 52   16 B1 (0.69 0.19 0.096 0.019 0) *
##                       739) reimbursement2008< 1485 11    6 B2 (0.36 0.45 0.18 0 0) *
##                   185) age< 39.5 22   10 B1 (0.55 0.27 0.045 0.045 0.091) *
##                  93) kidney>=0.5 58   26 B1 (0.55 0.24 0.16 0.052 0)  
##                   186) age< 69.5 15    2 B1 (0.87 0 0.13 0 0) *
##                   187) age>=69.5 43   24 B1 (0.44 0.33 0.16 0.07 0)  
##                     374) reimbursement2008< 1355 35   17 B1 (0.51 0.26 0.14 0.086 0)  
##                       748) reimbursement2008>=895 28   12 B1 (0.57 0.25 0.071 0.11 0) *
##                       749) reimbursement2008< 895 7    4 B3 (0.29 0.29 0.43 0 0) *
##                     375) reimbursement2008>=1355 8    3 B2 (0.12 0.62 0.25 0 0) *
##                47) diabetes>=0.5 819  298 B1 (0.64 0.23 0.09 0.044 0.0024)  
##                  94) reimbursement2008< 1155 412  126 B1 (0.69 0.19 0.083 0.029 0.0024)  
##                   188) osteoporosis>=0.5 90   19 B1 (0.79 0.11 0.078 0.022 0) *
##                   189) osteoporosis< 0.5 322  107 B1 (0.67 0.21 0.084 0.031 0.0031)  
##                     378) age>=46.5 310   99 B1 (0.68 0.21 0.077 0.029 0.0032)  
##                       756) reimbursement2008>=835 213   61 B1 (0.71 0.19 0.08 0.014 0.0047)  
##                        1512) age>=79.5 74   17 B1 (0.77 0.12 0.068 0.041 0) *
##                        1513) age< 79.5 139   44 B1 (0.68 0.22 0.086 0 0.0072)  
##                          3026) reimbursement2008>=1105 14    1 B1 (0.93 0.071 0 0 0) *
##                          3027) reimbursement2008< 1105 125   43 B1 (0.66 0.24 0.096 0 0.008)  
##                            6054) arthritis>=0.5 10    1 B1 (0.9 0.1 0 0 0) *
##                            6055) arthritis< 0.5 115   42 B1 (0.63 0.25 0.1 0 0.0087)  
##                             12110) age>=73.5 36   14 B1 (0.61 0.36 0.028 0 0)  
##                               24220) reimbursement2008< 1005 28    9 B1 (0.68 0.29 0.036 0 0) *
##                               24221) reimbursement2008>=1005 8    3 B2 (0.38 0.62 0 0 0) *
##                             12111) age< 73.5 79   28 B1 (0.65 0.2 0.14 0 0.013)  
##                               24222) age< 71.5 65   24 B1 (0.63 0.25 0.11 0 0.015)  
##                                 48444) reimbursement2008< 1075 58   20 B1 (0.66 0.21 0.12 0 0.017) *
##                                 48445) reimbursement2008>=1075 7    3 B2 (0.43 0.57 0 0 0) *
##                               24223) age>=71.5 14    4 B1 (0.71 0 0.29 0 0) *
##                       757) reimbursement2008< 835 97   38 B1 (0.61 0.26 0.072 0.062 0)  
##                        1514) age< 80.5 68   23 B1 (0.66 0.19 0.074 0.074 0)  
##                          3028) kidney>=0.5 9    4 B2 (0.44 0.56 0 0 0) *
##                          3029) kidney< 0.5 59   18 B1 (0.69 0.14 0.085 0.085 0) *
##                        1515) age>=80.5 29   15 B1 (0.48 0.41 0.069 0.034 0)  
##                          3030) age>=83.5 20    9 B1 (0.55 0.35 0.05 0.05 0) *
##                          3031) age< 83.5 9    4 B2 (0.33 0.56 0.11 0 0) *
##                     379) age< 46.5 12    8 B1 (0.33 0.33 0.25 0.083 0) *
##                  95) reimbursement2008>=1155 407  172 B1 (0.58 0.26 0.098 0.059 0.0025)  
##                   190) age< 89.5 382  155 B1 (0.59 0.25 0.094 0.058 0.0026)  
##                     380) reimbursement2008>=1175 352  141 B1 (0.6 0.26 0.085 0.051 0)  
##                       760) depression< 0.5 242   90 B1 (0.63 0.27 0.054 0.05 0) *
##                       761) depression>=0.5 110   51 B1 (0.54 0.25 0.15 0.055 0)  
##                        1522) age< 70.5 54   20 B1 (0.63 0.19 0.11 0.074 0) *
##                        1523) age>=70.5 56   31 B1 (0.45 0.32 0.2 0.036 0)  
##                          3046) age>=76.5 31   14 B1 (0.55 0.16 0.23 0.065 0) *
##                          3047) age< 76.5 25   12 B2 (0.32 0.52 0.16 0 0)  
##                            6094) reimbursement2008< 1435 18    8 B2 (0.44 0.56 0 0 0) *
##                            6095) reimbursement2008>=1435 7    3 B3 (0 0.43 0.57 0 0) *
##                     381) reimbursement2008< 1175 30   14 B1 (0.53 0.1 0.2 0.13 0.033)  
##                       762) age>=70 22    8 B1 (0.64 0.091 0.18 0.045 0.045) *
##                       763) age< 70 8    5 B4 (0.25 0.12 0.25 0.38 0) *
##                   191) age>=89.5 25   14 B2 (0.32 0.44 0.16 0.08 0)  
##                     382) depression>=0.5 7    2 B1 (0.71 0.14 0.14 0 0) *
##                     383) depression< 0.5 18    8 B2 (0.17 0.56 0.17 0.11 0) *
##         3) reimbursement2008>=1565 7858 4988 B2 (0.36 0.37 0.17 0.089 0.012)  
##           6) reimbursement2008< 3425 3262 1635 B1 (0.5 0.32 0.13 0.048 0.0049)  
##            12) ihd< 0.5 1087  442 B1 (0.59 0.26 0.11 0.033 0.0037)  
##              24) kidney< 0.5 941  358 B1 (0.62 0.24 0.1 0.031 0.0043)  
##                48) heart.failure< 0.5 680  234 B1 (0.66 0.23 0.087 0.029 0.0029)  
##                  96) reimbursement2008< 2605 524  172 B1 (0.67 0.2 0.099 0.031 0.0019)  
##                   192) age< 96.5 517  167 B1 (0.68 0.19 0.097 0.031 0.0019)  
##                     384) depression< 0.5 395  119 B1 (0.7 0.18 0.099 0.023 0.0025)  
##                       768) age>=68.5 288   79 B1 (0.73 0.15 0.097 0.028 0)  
##                        1536) arthritis>=0.5 47   11 B1 (0.77 0.064 0.17 0 0)  
##                          3072) reimbursement2008>=1655 40    7 B1 (0.82 0.075 0.1 0 0) *
##                          3073) reimbursement2008< 1655 7    3 B3 (0.43 0 0.57 0 0) *
##                        1537) arthritis< 0.5 241   68 B1 (0.72 0.17 0.083 0.033 0) *
##                       769) age< 68.5 107   40 B1 (0.63 0.25 0.1 0.0093 0.0093)  
##                        1538) arthritis< 0.5 92   31 B1 (0.66 0.24 0.076 0.011 0.011)  
##                          3076) osteoporosis>=0.5 23    5 B1 (0.78 0.13 0.043 0.043 0) *
##                          3077) osteoporosis< 0.5 69   26 B1 (0.62 0.28 0.087 0 0.014)  
##                            6154) reimbursement2008< 2295 59   20 B1 (0.66 0.25 0.068 0 0.017)  
##                             12308) reimbursement2008>=2050 15    2 B1 (0.87 0.13 0 0 0) *
##                             12309) reimbursement2008< 2050 44   18 B1 (0.59 0.3 0.091 0 0.023)  
##                               24618) diabetes>=0.5 16    4 B1 (0.75 0.12 0.12 0 0) *
##                               24619) diabetes< 0.5 28   14 B1 (0.5 0.39 0.071 0 0.036)  
##                                 49238) reimbursement2008< 1880 20    7 B1 (0.65 0.35 0 0 0) *
##                                 49239) reimbursement2008>=1880 8    4 B2 (0.12 0.5 0.25 0 0.12) *
##                            6155) reimbursement2008>=2295 10    6 B1 (0.4 0.4 0.2 0 0) *
##                        1539) arthritis>=0.5 15    9 B1 (0.4 0.33 0.27 0 0) *
##                     385) depression>=0.5 122   48 B1 (0.61 0.25 0.09 0.057 0)  
##                       770) age< 64 22    2 B1 (0.91 0.091 0 0 0) *
##                       771) age>=64 100   46 B1 (0.54 0.28 0.11 0.07 0)  
##                        1542) age< 79.5 72   29 B1 (0.6 0.29 0.083 0.028 0)  
##                          3084) arthritis< 0.5 58   24 B1 (0.59 0.34 0.069 0 0)  
##                            6168) reimbursement2008< 2415 49   19 B1 (0.61 0.31 0.082 0 0)  
##                             12336) reimbursement2008>=2155 11    2 B1 (0.82 0.18 0 0 0) *
##                             12337) reimbursement2008< 2155 38   17 B1 (0.55 0.34 0.11 0 0)  
##                               24674) reimbursement2008< 2020 29   11 B1 (0.62 0.31 0.069 0 0) *
##                               24675) reimbursement2008>=2020 9    5 B2 (0.33 0.44 0.22 0 0) *
##                            6169) reimbursement2008>=2415 9    4 B2 (0.44 0.56 0 0 0) *
##                          3085) arthritis>=0.5 14    5 B1 (0.64 0.071 0.14 0.14 0) *
##                        1543) age>=79.5 28   17 B1 (0.39 0.25 0.18 0.18 0)  
##                          3086) arthritis>=0.5 7    2 B1 (0.71 0.14 0 0.14 0) *
##                          3087) arthritis< 0.5 21   15 B1 (0.29 0.29 0.24 0.19 0)  
##                            6174) reimbursement2008< 2170 13    8 B2 (0.31 0.38 0.23 0.077 0) *
##                            6175) reimbursement2008>=2170 8    5 B4 (0.25 0.12 0.25 0.38 0) *
##                   193) age>=96.5 7    4 B2 (0.29 0.43 0.29 0 0) *
##                  97) reimbursement2008>=2605 156   62 B1 (0.6 0.32 0.045 0.026 0.0064)  
##                   194) arthritis< 0.5 118   40 B1 (0.66 0.26 0.051 0.017 0.0085)  
##                     388) age< 69.5 45   11 B1 (0.76 0.18 0.044 0.022 0) *
##                     389) age>=69.5 73   29 B1 (0.6 0.32 0.055 0.014 0.014)  
##                       778) reimbursement2008< 3390 66   27 B1 (0.59 0.35 0.045 0 0.015)  
##                        1556) age< 80.5 41   17 B1 (0.59 0.41 0 0 0)  
##                          3112) reimbursement2008>=2765 30   10 B1 (0.67 0.33 0 0 0)  
##                            6224) age< 77.5 23    5 B1 (0.78 0.22 0 0 0) *
##                            6225) age>=77.5 7    2 B2 (0.29 0.71 0 0 0) *
##                          3113) reimbursement2008< 2765 11    4 B2 (0.36 0.64 0 0 0) *
##                        1557) age>=80.5 25   10 B1 (0.6 0.24 0.12 0 0.04)  
##                          3114) reimbursement2008< 3090 18    5 B1 (0.72 0.11 0.17 0 0) *
##                          3115) reimbursement2008>=3090 7    3 B2 (0.29 0.57 0 0 0.14) *
##                       779) reimbursement2008>=3390 7    2 B1 (0.71 0 0.14 0.14 0) *
##                   195) arthritis>=0.5 38   19 B2 (0.42 0.5 0.026 0.053 0)  
##                     390) diabetes< 0.5 12    4 B1 (0.67 0.25 0 0.083 0) *
##                     391) diabetes>=0.5 26   10 B2 (0.31 0.62 0.038 0.038 0)  
##                       782) depression>=0.5 7    3 B1 (0.57 0.43 0 0 0) *
##                       783) depression< 0.5 19    6 B2 (0.21 0.68 0.053 0.053 0) *
##                49) heart.failure>=0.5 261  124 B1 (0.52 0.29 0.14 0.034 0.0077)  
##                  98) diabetes< 0.5 110   42 B1 (0.62 0.24 0.082 0.055 0.0091)  
##                   196) depression>=0.5 32    8 B1 (0.75 0.12 0.12 0 0) *
##                   197) depression< 0.5 78   34 B1 (0.56 0.28 0.064 0.077 0.013)  
##                     394) reimbursement2008>=2685 20    5 B1 (0.75 0.15 0 0.1 0) *
##                     395) reimbursement2008< 2685 58   29 B1 (0.5 0.33 0.086 0.069 0.017)  
##                       790) reimbursement2008< 2425 50   23 B1 (0.54 0.32 0.04 0.08 0.02)  
##                        1580) age>=71.5 26    9 B1 (0.65 0.27 0.038 0 0.038) *
##                        1581) age< 71.5 24   14 B1 (0.42 0.38 0.042 0.17 0)  
##                          3162) age< 68.5 17    8 B1 (0.53 0.29 0.059 0.12 0) *
##                          3163) age>=68.5 7    3 B2 (0.14 0.57 0 0.29 0) *
##                       791) reimbursement2008>=2425 8    5 B2 (0.25 0.38 0.38 0 0) *
##                  99) diabetes>=0.5 151   82 B1 (0.46 0.33 0.19 0.02 0.0066)  
##                   198) reimbursement2008>=1675 140   74 B1 (0.47 0.31 0.19 0.021 0.0071)  
##                     396) reimbursement2008< 1775 10    3 B1 (0.7 0 0.3 0 0) *
##                     397) reimbursement2008>=1775 130   71 B1 (0.45 0.33 0.18 0.023 0.0077)  
##                       794) reimbursement2008>=3265 9    2 B1 (0.78 0.11 0.11 0 0) *
##                       795) reimbursement2008< 3265 121   69 B1 (0.43 0.35 0.19 0.025 0.0083)  
##                        1590) reimbursement2008< 3190 113   62 B1 (0.45 0.33 0.19 0.027 0.0088)  
##                          3180) reimbursement2008>=3055 8    1 B1 (0.88 0 0 0.12 0) *
##                          3181) reimbursement2008< 3055 105   61 B1 (0.42 0.35 0.2 0.019 0.0095)  
##                            6362) age>=75.5 45   22 B1 (0.51 0.29 0.18 0 0.022)  
##                             12724) arthritis< 0.5 32   13 B1 (0.59 0.19 0.19 0 0.031) *
##                             12725) arthritis>=0.5 13    6 B2 (0.31 0.54 0.15 0 0) *
##                            6363) age< 75.5 60   36 B2 (0.35 0.4 0.22 0.033 0)  
##                             12726) reimbursement2008>=2215 36   20 B1 (0.44 0.28 0.22 0.056 0)  
##                               25452) reimbursement2008< 2400 12    5 B1 (0.58 0.083 0.33 0 0) *
##                               25453) reimbursement2008>=2400 24   15 B1 (0.38 0.38 0.17 0.083 0)  
##                                 50906) age< 70 16    9 B2 (0.38 0.44 0.19 0 0) *
##                                 50907) age>=70 8    5 B1 (0.38 0.25 0.12 0.25 0) *
##                             12727) reimbursement2008< 2215 24   10 B2 (0.21 0.58 0.21 0 0) *
##                        1591) reimbursement2008>=3190 8    3 B2 (0.12 0.62 0.25 0 0) *
##                   199) reimbursement2008< 1675 11    4 B2 (0.27 0.64 0.091 0 0) *
##              25) kidney>=0.5 146   84 B1 (0.42 0.34 0.18 0.048 0)  
##                50) age< 74.5 82   38 B1 (0.54 0.27 0.15 0.049 0)  
##                 100) age>=63.5 63   25 B1 (0.6 0.19 0.14 0.063 0) *
##                 101) age< 63.5 19    9 B2 (0.32 0.53 0.16 0 0) *
##                51) age>=74.5 64   36 B2 (0.28 0.44 0.23 0.047 0)  
##                 102) age>=84.5 28   12 B2 (0.32 0.57 0.071 0.036 0) *
##                 103) age< 84.5 36   23 B3 (0.25 0.33 0.36 0.056 0)  
##                   206) reimbursement2008< 1990 10    4 B1 (0.6 0.2 0.2 0 0) *
##                   207) reimbursement2008>=1990 26   15 B3 (0.12 0.38 0.42 0.077 0)  
##                     414) age< 78.5 12    5 B2 (0.17 0.58 0.17 0.083 0) *
##                     415) age>=78.5 14    5 B3 (0.071 0.21 0.64 0.071 0) *
##            13) ihd>=0.5 2175 1193 B1 (0.45 0.35 0.13 0.055 0.0055)  
##              26) reimbursement2008< 2515 1275  637 B1 (0.5 0.32 0.12 0.053 0.0063)  
##                52) depression< 0.5 880  412 B1 (0.53 0.29 0.12 0.052 0.008)  
##                 104) stroke< 0.5 849  390 B1 (0.54 0.29 0.11 0.053 0.0082)  
##                   208) age>=73.5 406  162 B1 (0.6 0.26 0.086 0.047 0.0074)  
##                     416) arthritis< 0.5 307  115 B1 (0.63 0.23 0.091 0.046 0.0065)  
##                       832) diabetes>=0.5 163   55 B1 (0.66 0.17 0.11 0.049 0.0061) *
##                       833) diabetes< 0.5 144   60 B1 (0.58 0.3 0.069 0.042 0.0069)  
##                        1666) heart.failure< 0.5 86   31 B1 (0.64 0.22 0.081 0.047 0.012)  
##                          3332) alzheimers< 0.5 70   21 B1 (0.7 0.17 0.071 0.043 0.014) *
##                          3333) alzheimers>=0.5 16    9 B2 (0.38 0.44 0.12 0.062 0) *
##                        1667) heart.failure>=0.5 58   29 B1 (0.5 0.41 0.052 0.034 0)  
##                          3334) age< 75.5 8    2 B1 (0.75 0.12 0.12 0 0) *
##                          3335) age>=75.5 50   27 B1 (0.46 0.46 0.04 0.04 0)  
##                            6670) age< 89.5 42   21 B1 (0.5 0.43 0.048 0.024 0)  
##                             13340) reimbursement2008< 2305 34   15 B1 (0.56 0.41 0.029 0 0)  
##                               26680) reimbursement2008>=2070 7    2 B1 (0.71 0.14 0.14 0 0) *
##                               26681) reimbursement2008< 2070 27   13 B1 (0.52 0.48 0 0 0)  
##                                 53362) age>=79.5 20    8 B1 (0.6 0.4 0 0 0)  
##                                  106724) reimbursement2008< 1790 9    2 B1 (0.78 0.22 0 0 0) *
##                                  106725) reimbursement2008>=1790 11    5 B2 (0.45 0.55 0 0 0) *
##                                 53363) age< 79.5 7    2 B2 (0.29 0.71 0 0 0) *
##                             13341) reimbursement2008>=2305 8    4 B2 (0.25 0.5 0.12 0.12 0) *
##                            6671) age>=89.5 8    3 B2 (0.25 0.62 0 0.12 0) *
##                     417) arthritis>=0.5 99   47 B1 (0.53 0.34 0.071 0.051 0.01)  
##                       834) copd>=0.5 11    2 B1 (0.82 0.091 0.091 0 0) *
##                       835) copd< 0.5 88   45 B1 (0.49 0.38 0.068 0.057 0.011)  
##                        1670) alzheimers< 0.5 63   32 B1 (0.49 0.43 0.063 0 0.016)  
##                          3340) reimbursement2008< 2015 33   14 B1 (0.58 0.3 0.091 0 0.03)  
##                            6680) age>=77.5 19    5 B1 (0.74 0.16 0.11 0 0) *
##                            6681) age< 77.5 14    7 B2 (0.36 0.5 0.071 0 0.071) *
##                          3341) reimbursement2008>=2015 30   13 B2 (0.4 0.57 0.033 0 0)  
##                            6682) osteoporosis>=0.5 12    5 B1 (0.58 0.42 0 0 0) *
##                            6683) osteoporosis< 0.5 18    6 B2 (0.28 0.67 0.056 0 0) *
##                        1671) alzheimers>=0.5 25   13 B1 (0.48 0.24 0.08 0.2 0)  
##                          3342) diabetes< 0.5 10    2 B1 (0.8 0 0.1 0.1 0) *
##                          3343) diabetes>=0.5 15    9 B2 (0.27 0.4 0.067 0.27 0) *
##                   209) age< 73.5 443  228 B1 (0.49 0.32 0.13 0.059 0.009)  
##                     418) heart.failure< 0.5 261  117 B1 (0.55 0.28 0.11 0.057 0.0038)  
##                       836) kidney< 0.5 228   93 B1 (0.59 0.27 0.088 0.048 0.0044)  
##                        1672) age>=43.5 218   85 B1 (0.61 0.26 0.083 0.046 0.0046)  
##                          3344) reimbursement2008< 2485 211   80 B1 (0.62 0.24 0.085 0.047 0.0047)  
##                            6688) diabetes< 0.5 96   29 B1 (0.7 0.2 0.073 0.031 0) *
##                            6689) diabetes>=0.5 115   51 B1 (0.56 0.28 0.096 0.061 0.0087)  
##                             13378) age< 60 20    5 B1 (0.75 0.25 0 0 0) *
##                             13379) age>=60 95   46 B1 (0.52 0.28 0.12 0.074 0.011)  
##                               26758) reimbursement2008< 1735 27    8 B1 (0.7 0.15 0.11 0 0.037) *
##                               26759) reimbursement2008>=1735 68   38 B1 (0.44 0.34 0.12 0.1 0)  
##                                 53518) reimbursement2008>=2145 29   13 B1 (0.55 0.24 0.17 0.034 0)  
##                                  107036) age>=69.5 17    5 B1 (0.71 0.12 0.18 0 0) *
##                                  107037) age< 69.5 12    7 B2 (0.33 0.42 0.17 0.083 0) *
##                                 53519) reimbursement2008< 2145 39   23 B2 (0.36 0.41 0.077 0.15 0)  
##                                  107038) reimbursement2008< 2065 30   17 B1 (0.43 0.37 0.067 0.13 0)  
##                                    214076) reimbursement2008>=1910 12    4 B1 (0.67 0.17 0 0.17 0) *
##                                    214077) reimbursement2008< 1910 18    9 B2 (0.28 0.5 0.11 0.11 0) *
##                                  107039) reimbursement2008>=2065 9    4 B2 (0.11 0.56 0.11 0.22 0) *
##                          3345) reimbursement2008>=2485 7    2 B2 (0.29 0.71 0 0 0) *
##                        1673) age< 43.5 10    5 B2 (0.2 0.5 0.2 0.1 0) *
##                       837) kidney>=0.5 33   21 B2 (0.27 0.36 0.24 0.12 0)  
##                        1674) age< 72.5 26   16 B2 (0.35 0.38 0.12 0.15 0)  
##                          3348) age>=54.5 18   10 B1 (0.44 0.28 0.11 0.17 0) *
##                          3349) age< 54.5 8    3 B2 (0.12 0.62 0.12 0.12 0) *
##                        1675) age>=72.5 7    2 B3 (0 0.29 0.71 0 0) *
##                     419) heart.failure>=0.5 182  111 B1 (0.39 0.37 0.16 0.06 0.016)  
##                       838) copd< 0.5 146   85 B2 (0.38 0.42 0.13 0.055 0.014)  
##                        1676) reimbursement2008< 2235 115   67 B1 (0.42 0.4 0.096 0.07 0.017)  
##                          3352) age>=55.5 98   56 B2 (0.42 0.43 0.061 0.082 0.01)  
##                            6704) reimbursement2008< 2165 88   48 B2 (0.41 0.45 0.068 0.057 0.011)  
##                             13408) reimbursement2008< 1925 55   29 B1 (0.47 0.44 0.036 0.055 0)  
##                               26816) reimbursement2008< 1865 45   23 B2 (0.44 0.49 0.044 0.022 0)  
##                                 53632) age>=66.5 33   16 B1 (0.52 0.42 0.03 0.03 0)  
##                                  107264) reimbursement2008< 1715 18    7 B1 (0.61 0.33 0 0.056 0) *
##                                  107265) reimbursement2008>=1715 15    7 B2 (0.4 0.53 0.067 0 0) *
##                                 53633) age< 66.5 12    4 B2 (0.25 0.67 0.083 0 0) *
##                               26817) reimbursement2008>=1865 10    4 B1 (0.6 0.2 0 0.2 0) *
##                             13409) reimbursement2008>=1925 33   17 B2 (0.3 0.48 0.12 0.061 0.03)  
##                               26818) age>=72.5 7    1 B2 (0.14 0.86 0 0 0) *
##                               26819) age< 72.5 26   16 B2 (0.35 0.38 0.15 0.077 0.038)  
##                                 53638) reimbursement2008>=2005 14    7 B1 (0.5 0.36 0.071 0.071 0) *
##                                 53639) reimbursement2008< 2005 12    7 B2 (0.17 0.42 0.25 0.083 0.083) *
##                            6705) reimbursement2008>=2165 10    5 B1 (0.5 0.2 0 0.3 0) *
##                          3353) age< 55.5 17   10 B1 (0.41 0.24 0.29 0 0.059) *
##                        1677) reimbursement2008>=2235 31   16 B2 (0.26 0.48 0.26 0 0)  
##                          3354) age>=62 23   14 B2 (0.35 0.39 0.26 0 0)  
##                            6708) reimbursement2008>=2305 16    8 B2 (0.31 0.5 0.19 0 0) *
##                            6709) reimbursement2008< 2305 7    4 B1 (0.43 0.14 0.43 0 0) *
##                          3355) age< 62 8    2 B2 (0 0.75 0.25 0 0) *
##                       839) copd>=0.5 36   21 B1 (0.42 0.19 0.28 0.083 0.028)  
##                        1678) age>=69.5 11    5 B1 (0.55 0.36 0.091 0 0) *
##                        1679) age< 69.5 25   16 B1 (0.36 0.12 0.36 0.12 0.04)  
##                          3358) diabetes< 0.5 8    4 B1 (0.5 0.12 0.12 0.25 0) *
##                          3359) diabetes>=0.5 17    9 B3 (0.29 0.12 0.47 0.059 0.059) *
##                 105) stroke>=0.5 31   20 B2 (0.29 0.35 0.32 0.032 0)  
##                   210) age>=75.5 17    8 B2 (0.24 0.53 0.24 0 0) *
##                   211) age< 75.5 14    8 B3 (0.36 0.14 0.43 0.071 0) *
##                53) depression>=0.5 395  225 B1 (0.43 0.38 0.13 0.056 0.0025)  
##                 106) age>=84.5 80   34 B1 (0.57 0.29 0.062 0.075 0)  
##                   212) age< 93.5 55   18 B1 (0.67 0.22 0.055 0.055 0) *
##                   213) age>=93.5 25   14 B2 (0.36 0.44 0.08 0.12 0)  
##                     426) age>=97.5 15    8 B1 (0.47 0.27 0.13 0.13 0) *
##                     427) age< 97.5 10    3 B2 (0.2 0.7 0 0.1 0) *
##                 107) age< 84.5 315  186 B2 (0.39 0.41 0.14 0.051 0.0032)  
##                   214) cancer< 0.5 298  176 B1 (0.41 0.39 0.14 0.05 0.0034)  
##                     428) age< 71.5 162   86 B1 (0.47 0.33 0.12 0.074 0.0062)  
##                       856) reimbursement2008< 1975 76   28 B1 (0.63 0.24 0.053 0.066 0.013)  
##                        1712) copd< 0.5 62   20 B1 (0.68 0.18 0.065 0.065 0.016)  
##                          3424) heart.failure>=0.5 28    6 B1 (0.79 0.036 0.071 0.071 0.036) *
##                          3425) heart.failure< 0.5 34   14 B1 (0.59 0.29 0.059 0.059 0)  
##                            6850) reimbursement2008>=1865 10    2 B1 (0.8 0 0.1 0.1 0) *
##                            6851) reimbursement2008< 1865 24   12 B1 (0.5 0.42 0.042 0.042 0)  
##                             13702) reimbursement2008< 1775 14    4 B1 (0.71 0.29 0 0 0) *
##                             13703) reimbursement2008>=1775 10    4 B2 (0.2 0.6 0.1 0.1 0) *
##                        1713) copd>=0.5 14    7 B2 (0.43 0.5 0 0.071 0) *
##                       857) reimbursement2008>=1975 86   51 B2 (0.33 0.41 0.19 0.081 0)  
##                        1714) alzheimers< 0.5 54   33 B1 (0.39 0.31 0.22 0.074 0)  
##                          3428) reimbursement2008>=2305 25   11 B1 (0.56 0.28 0.12 0.04 0) *
##                          3429) reimbursement2008< 2305 29   19 B2 (0.24 0.34 0.31 0.1 0)  
##                            6858) age>=55 22   12 B2 (0.18 0.45 0.27 0.091 0) *
##                            6859) age< 55 7    4 B1 (0.43 0 0.43 0.14 0) *
##                        1715) alzheimers>=0.5 32   14 B2 (0.22 0.56 0.12 0.094 0) *
##                     429) age>=71.5 136   72 B2 (0.34 0.47 0.17 0.022 0)  
##                       858) reimbursement2008>=1705 117   57 B2 (0.33 0.51 0.15 0.0085 0)  
##                        1716) reimbursement2008>=2445 8    3 B1 (0.62 0.25 0.12 0 0) *
##                        1717) reimbursement2008< 2445 109   51 B2 (0.31 0.53 0.15 0.0092 0)  
##                          3434) reimbursement2008>=2375 10    2 B2 (0.2 0.8 0 0 0) *
##                          3435) reimbursement2008< 2375 99   49 B2 (0.32 0.51 0.16 0.01 0)  
##                            6870) reimbursement2008>=2045 46   27 B1 (0.41 0.41 0.17 0 0)  
##                             13740) copd>=0.5 7    2 B1 (0.71 0 0.29 0 0) *
##                             13741) copd< 0.5 39   20 B2 (0.36 0.49 0.15 0 0)  
##                               27482) heart.failure>=0.5 15    6 B1 (0.6 0.33 0.067 0 0) *
##                               27483) heart.failure< 0.5 24   10 B2 (0.21 0.58 0.21 0 0) *
##                            6871) reimbursement2008< 2045 53   22 B2 (0.25 0.58 0.15 0.019 0)  
##                             13742) reimbursement2008< 1795 13    6 B1 (0.54 0.46 0 0 0) *
##                             13743) reimbursement2008>=1795 40   15 B2 (0.15 0.62 0.2 0.025 0)  
##                               27486) age< 78.5 33   10 B2 (0.12 0.7 0.15 0.03 0) *
##                               27487) age>=78.5 7    4 B3 (0.29 0.29 0.43 0 0) *
##                       859) reimbursement2008< 1705 19   12 B1 (0.37 0.21 0.32 0.11 0) *
##                   215) cancer>=0.5 17    5 B2 (0.12 0.71 0.12 0.059 0) *
##              27) reimbursement2008>=2515 900  539 B2 (0.38 0.4 0.16 0.057 0.0044)  
##                54) arthritis< 0.5 614  349 B1 (0.43 0.35 0.15 0.06 0.0033)  
##                 108) heart.failure< 0.5 317  155 B1 (0.51 0.32 0.13 0.038 0.0063)  
##                   216) cancer< 0.5 281  127 B1 (0.55 0.28 0.12 0.043 0.0071)  
##                     432) age< 67.5 68   24 B1 (0.65 0.26 0.044 0.044 0)  
##                       864) age>=64.5 21    3 B1 (0.86 0.095 0 0.048 0) *
##                       865) age< 64.5 47   21 B1 (0.55 0.34 0.064 0.043 0)  
##                        1730) reimbursement2008>=2765 37   15 B1 (0.59 0.27 0.081 0.054 0) *
##                        1731) reimbursement2008< 2765 10    4 B2 (0.4 0.6 0 0 0) *
##                     433) age>=67.5 213  103 B1 (0.52 0.28 0.15 0.042 0.0094)  
##                       866) diabetes< 0.5 92   35 B1 (0.62 0.23 0.11 0.043 0)  
##                        1732) reimbursement2008>=3170 23    4 B1 (0.83 0.087 0.087 0 0) *
##                        1733) reimbursement2008< 3170 69   31 B1 (0.55 0.28 0.12 0.058 0)  
##                          3466) alzheimers>=0.5 14    3 B1 (0.79 0.14 0 0.071 0) *
##                          3467) alzheimers< 0.5 55   28 B1 (0.49 0.31 0.15 0.055 0)  
##                            6934) age< 83.5 41   23 B1 (0.44 0.41 0.15 0 0)  
##                             13868) reimbursement2008>=2680 30   14 B1 (0.53 0.37 0.1 0 0)  
##                               27736) depression< 0.5 22    8 B1 (0.64 0.32 0.045 0 0) *
##                               27737) depression>=0.5 8    4 B2 (0.25 0.5 0.25 0 0) *
##                             13869) reimbursement2008< 2680 11    5 B2 (0.18 0.55 0.27 0 0) *
##                            6935) age>=83.5 14    5 B1 (0.64 0 0.14 0.21 0) *
##                       867) diabetes>=0.5 121   68 B1 (0.44 0.32 0.18 0.041 0.017)  
##                        1734) age>=69.5 104   54 B1 (0.48 0.28 0.18 0.038 0.019)  
##                          3468) age< 79.5 58   25 B1 (0.57 0.19 0.17 0.034 0.034)  
##                            6936) reimbursement2008>=3325 7    0 B1 (1 0 0 0 0) *
##                            6937) reimbursement2008< 3325 51   25 B1 (0.51 0.22 0.2 0.039 0.039)  
##                             13874) reimbursement2008< 2865 24    9 B1 (0.62 0.12 0.21 0 0.042) *
##                             13875) reimbursement2008>=2865 27   16 B1 (0.41 0.3 0.19 0.074 0.037)  
##                               27750) reimbursement2008>=3040 20   10 B1 (0.5 0.3 0.1 0.1 0)  
##                                 55500) alzheimers>=0.5 8    2 B1 (0.75 0.12 0 0.12 0) *
##                                 55501) alzheimers< 0.5 12    7 B2 (0.33 0.42 0.17 0.083 0) *
##                               27751) reimbursement2008< 3040 7    4 B3 (0.14 0.29 0.43 0 0.14) *
##                          3469) age>=79.5 46   28 B2 (0.37 0.39 0.2 0.043 0)  
##                            6938) kidney< 0.5 33   18 B2 (0.39 0.45 0.12 0.03 0)  
##                             13876) osteoporosis>=0.5 7    2 B2 (0.29 0.71 0 0 0) *
##                             13877) osteoporosis< 0.5 26   15 B1 (0.42 0.38 0.15 0.038 0)  
##                               27754) reimbursement2008< 2785 12    5 B2 (0.33 0.58 0.083 0 0) *
##                               27755) reimbursement2008>=2785 14    7 B1 (0.5 0.21 0.21 0.071 0) *
##                            6939) kidney>=0.5 13    8 B3 (0.31 0.23 0.38 0.077 0) *
##                        1735) age< 69.5 17    7 B2 (0.18 0.59 0.18 0.059 0) *
##                   217) cancer>=0.5 36   14 B2 (0.22 0.61 0.17 0 0)  
##                     434) reimbursement2008< 2770 10    5 B1 (0.5 0.3 0.2 0 0) *
##                     435) reimbursement2008>=2770 26    7 B2 (0.12 0.73 0.15 0 0) *
##                 109) heart.failure>=0.5 297  181 B2 (0.35 0.39 0.18 0.084 0)  
##                   218) kidney< 0.5 213  130 B1 (0.39 0.35 0.15 0.1 0)  
##                     436) alzheimers< 0.5 146   81 B1 (0.45 0.36 0.11 0.089 0)  
##                       872) reimbursement2008>=2585 133   70 B1 (0.47 0.36 0.083 0.083 0)  
##                        1744) reimbursement2008>=3365 8    1 B1 (0.88 0.12 0 0 0) *
##                        1745) reimbursement2008< 3365 125   69 B1 (0.45 0.38 0.088 0.088 0)  
##                          3490) reimbursement2008< 2925 67   31 B1 (0.54 0.27 0.09 0.1 0)  
##                            6980) diabetes< 0.5 23    8 B1 (0.65 0.087 0.13 0.13 0) *
##                            6981) diabetes>=0.5 44   23 B1 (0.48 0.36 0.068 0.091 0)  
##                             13962) reimbursement2008< 2715 23   12 B2 (0.43 0.48 0.043 0.043 0)  
##                               27924) reimbursement2008< 2630 9    3 B1 (0.67 0.22 0 0.11 0) *
##                               27925) reimbursement2008>=2630 14    5 B2 (0.29 0.64 0.071 0 0) *
##                             13963) reimbursement2008>=2715 21   10 B1 (0.52 0.24 0.095 0.14 0)  
##                               27926) age>=71.5 12    4 B1 (0.67 0.083 0.083 0.17 0) *
##                               27927) age< 71.5 9    5 B2 (0.33 0.44 0.11 0.11 0) *
##                          3491) reimbursement2008>=2925 58   29 B2 (0.34 0.5 0.086 0.069 0)  
##                            6982) age< 67.5 13    5 B1 (0.62 0.31 0.077 0 0) *
##                            6983) age>=67.5 45   20 B2 (0.27 0.56 0.089 0.089 0)  
##                             13966) reimbursement2008>=3285 10    5 B1 (0.5 0.3 0.1 0.1 0) *
##                             13967) reimbursement2008< 3285 35   13 B2 (0.2 0.63 0.086 0.086 0) *
##                       873) reimbursement2008< 2585 13    8 B3 (0.15 0.31 0.38 0.15 0) *
##                     437) alzheimers>=0.5 67   44 B2 (0.27 0.34 0.25 0.13 0)  
##                       874) reimbursement2008< 2605 11    6 B1 (0.45 0.18 0.27 0.091 0) *
##                       875) reimbursement2008>=2605 56   35 B2 (0.23 0.38 0.25 0.14 0)  
##                        1750) reimbursement2008< 2755 10    3 B2 (0.1 0.7 0.1 0.1 0) *
##                        1751) reimbursement2008>=2755 46   32 B2 (0.26 0.3 0.28 0.15 0)  
##                          3502) reimbursement2008>=2845 39   27 B1 (0.31 0.31 0.23 0.15 0)  
##                            7004) reimbursement2008>=3120 19   10 B2 (0.21 0.47 0.21 0.11 0) *
##                            7005) reimbursement2008< 3120 20   12 B1 (0.4 0.15 0.25 0.2 0)  
##                             14010) reimbursement2008< 2955 8    3 B1 (0.62 0.25 0.12 0 0) *
##                             14011) reimbursement2008>=2955 12    8 B3 (0.25 0.083 0.33 0.33 0) *
##                          3503) reimbursement2008< 2845 7    3 B3 (0 0.29 0.57 0.14 0) *
##                   219) kidney>=0.5 84   43 B2 (0.24 0.49 0.24 0.036 0)  
##                     438) copd< 0.5 57   28 B2 (0.28 0.51 0.16 0.053 0)  
##                       876) reimbursement2008>=2735 41   16 B2 (0.22 0.61 0.15 0.024 0) *
##                       877) reimbursement2008< 2735 16    9 B1 (0.44 0.25 0.19 0.12 0) *
##                     439) copd>=0.5 27   15 B2 (0.15 0.44 0.41 0 0)  
##                       878) age>=84.5 9    5 B1 (0.44 0.22 0.33 0 0) *
##                       879) age< 84.5 18    8 B2 (0 0.56 0.44 0 0) *
##                55) arthritis>=0.5 286  141 B2 (0.28 0.51 0.16 0.049 0.007)  
##                 110) reimbursement2008< 3015 174   97 B2 (0.31 0.44 0.21 0.034 0.0057)  
##                   220) reimbursement2008< 2965 157   84 B2 (0.32 0.46 0.18 0.032 0.0064)  
##                     440) stroke< 0.5 150   83 B2 (0.33 0.45 0.18 0.033 0.0067)  
##                       880) age< 89.5 142   81 B2 (0.35 0.43 0.19 0.028 0.007)  
##                        1760) kidney< 0.5 104   57 B2 (0.37 0.45 0.13 0.038 0.0096)  
##                          3520) reimbursement2008>=2785 40   22 B1 (0.45 0.38 0.12 0.025 0.025)  
##                            7040) age< 80.5 32   15 B1 (0.53 0.34 0.12 0 0)  
##                             14080) depression< 0.5 18    6 B1 (0.67 0.22 0.11 0 0) *
##                             14081) depression>=0.5 14    7 B2 (0.36 0.5 0.14 0 0) *
##                            7041) age>=80.5 8    4 B2 (0.12 0.5 0.12 0.12 0.12) *
##                          3521) reimbursement2008< 2785 64   32 B2 (0.31 0.5 0.14 0.047 0)  
##                            7042) reimbursement2008>=2565 52   23 B2 (0.29 0.56 0.13 0.019 0) *
##                            7043) reimbursement2008< 2565 12    7 B1 (0.42 0.25 0.17 0.17 0) *
##                        1761) kidney>=0.5 38   24 B2 (0.29 0.37 0.34 0 0)  
##                          3522) alzheimers>=0.5 12    5 B2 (0.33 0.58 0.083 0 0) *
##                          3523) alzheimers< 0.5 26   14 B3 (0.27 0.27 0.46 0 0)  
##                            7046) diabetes>=0.5 19   12 B2 (0.32 0.37 0.32 0 0) *
##                            7047) diabetes< 0.5 7    1 B3 (0.14 0 0.86 0 0) *
##                       881) age>=89.5 8    2 B2 (0.12 0.75 0 0.12 0) *
##                     441) stroke>=0.5 7    1 B2 (0 0.86 0.14 0 0) *
##                   221) reimbursement2008>=2965 17    9 B3 (0.24 0.24 0.47 0.059 0) *
##                 111) reimbursement2008>=3015 112   44 B2 (0.22 0.61 0.089 0.071 0.0089)  
##                   222) kidney< 0.5 81   38 B2 (0.28 0.53 0.099 0.074 0.012)  
##                     444) reimbursement2008>=3075 70   35 B2 (0.31 0.5 0.11 0.057 0.014)  
##                       888) reimbursement2008< 3265 40   23 B1 (0.43 0.4 0.12 0.025 0.025)  
##                        1776) age>=82.5 11    4 B2 (0.27 0.64 0.091 0 0) *
##                        1777) age< 82.5 29   15 B1 (0.48 0.31 0.14 0.034 0.034)  
##                          3554) heart.failure< 0.5 11    2 B1 (0.82 0.18 0 0 0) *
##                          3555) heart.failure>=0.5 18   11 B2 (0.28 0.39 0.22 0.056 0.056) *
##                       889) reimbursement2008>=3265 30   11 B2 (0.17 0.63 0.1 0.1 0) *
##                     445) reimbursement2008< 3075 11    3 B2 (0.091 0.73 0 0.18 0) *
##                   223) kidney>=0.5 31    6 B2 (0.065 0.81 0.065 0.065 0) *
##           7) reimbursement2008>=3425 4596 2775 B2 (0.26 0.4 0.2 0.12 0.017)  
##            14) diabetes< 0.5 1002  558 B1 (0.44 0.33 0.17 0.054 0.003)  
##              28) depression< 0.5 682  335 B1 (0.51 0.3 0.14 0.048 0.0044)  
##                56) cancer< 0.5 563  252 B1 (0.55 0.28 0.13 0.036 0.0053)  
##                 112) arthritis< 0.5 419  169 B1 (0.6 0.26 0.1 0.031 0.0072)  
##                   224) osteoporosis< 0.5 330  125 B1 (0.62 0.23 0.11 0.03 0.0061)  
##                     448) ihd< 0.5 120   33 B1 (0.72 0.17 0.067 0.033 0)  
##                       896) reimbursement2008>=8195 26    2 B1 (0.92 0.038 0.038 0 0) *
##                       897) reimbursement2008< 8195 94   31 B1 (0.67 0.21 0.074 0.043 0)  
##                        1794) heart.failure< 0.5 64   17 B1 (0.73 0.16 0.062 0.047 0) *
##                        1795) heart.failure>=0.5 30   14 B1 (0.53 0.33 0.1 0.033 0)  
##                          3590) copd< 0.5 23    9 B1 (0.61 0.26 0.087 0.043 0) *
##                          3591) copd>=0.5 7    3 B2 (0.29 0.57 0.14 0 0) *
##                     449) ihd>=0.5 210   92 B1 (0.56 0.27 0.13 0.029 0.0095)  
##                       898) reimbursement2008>=7060 89   32 B1 (0.64 0.24 0.079 0.034 0.011)  
##                        1796) reimbursement2008< 9310 22    3 B1 (0.86 0.091 0.045 0 0) *
##                        1797) reimbursement2008>=9310 67   29 B1 (0.57 0.28 0.09 0.045 0.015)  
##                          3594) reimbursement2008>=10695 56   21 B1 (0.62 0.27 0.054 0.036 0.018) *
##                          3595) reimbursement2008< 10695 11    7 B2 (0.27 0.36 0.27 0.091 0) *
##                       899) reimbursement2008< 7060 121   60 B1 (0.5 0.29 0.17 0.025 0.0083)  
##                        1798) reimbursement2008< 6145 105   46 B1 (0.56 0.26 0.16 0.019 0)  
##                          3596) age>=88.5 8    1 B1 (0.88 0.12 0 0 0) *
##                          3597) age< 88.5 97   45 B1 (0.54 0.27 0.18 0.021 0)  
##                            7194) age< 81.5 79   33 B1 (0.58 0.22 0.19 0.013 0)  
##                             14388) reimbursement2008< 4235 32   14 B1 (0.56 0.34 0.062 0.031 0) *
##                             14389) reimbursement2008>=4235 47   19 B1 (0.6 0.13 0.28 0 0)  
##                               28778) age>=70.5 22    6 B1 (0.73 0.091 0.18 0 0) *
##                               28779) age< 70.5 25   13 B1 (0.48 0.16 0.36 0 0)  
##                                 57558) reimbursement2008< 5500 18    7 B1 (0.61 0.11 0.28 0 0) *
##                                 57559) reimbursement2008>=5500 7    3 B3 (0.14 0.29 0.57 0 0) *
##                            7195) age>=81.5 18    9 B2 (0.33 0.5 0.11 0.056 0) *
##                        1799) reimbursement2008>=6145 16    8 B2 (0.12 0.5 0.25 0.062 0.062) *
##                   225) osteoporosis>=0.5 89   44 B1 (0.51 0.38 0.067 0.034 0.011)  
##                     450) reimbursement2008>=12275 15    3 B1 (0.8 0.067 0.067 0.067 0) *
##                     451) reimbursement2008< 12275 74   41 B1 (0.45 0.45 0.068 0.027 0.014)  
##                       902) copd< 0.5 60   30 B1 (0.5 0.38 0.083 0.033 0)  
##                        1804) age< 74.5 26    9 B1 (0.65 0.27 0.077 0 0) *
##                        1805) age>=74.5 34   18 B2 (0.38 0.47 0.088 0.059 0)  
##                          3610) age< 83.5 22    9 B2 (0.32 0.59 0.045 0.045 0) *
##                          3611) age>=83.5 12    6 B1 (0.5 0.25 0.17 0.083 0) *
##                       903) copd>=0.5 14    4 B2 (0.21 0.71 0 0 0.071) *
##                 113) arthritis>=0.5 144   83 B1 (0.42 0.33 0.2 0.049 0)  
##                   226) age< 73.5 58   27 B1 (0.53 0.26 0.14 0.069 0)  
##                     452) reimbursement2008>=6600 27    8 B1 (0.7 0.15 0.037 0.11 0) *
##                     453) reimbursement2008< 6600 31   19 B1 (0.39 0.35 0.23 0.032 0)  
##                       906) heart.failure>=0.5 16    8 B2 (0.31 0.5 0.19 0 0) *
##                       907) heart.failure< 0.5 15    8 B1 (0.47 0.2 0.27 0.067 0) *
##                   227) age>=73.5 86   54 B2 (0.35 0.37 0.24 0.035 0)  
##                     454) ihd< 0.5 14    6 B1 (0.57 0.21 0.14 0.071 0) *
##                     455) ihd>=0.5 72   43 B2 (0.31 0.4 0.26 0.028 0)  
##                       910) reimbursement2008< 4780 18    7 B2 (0.22 0.61 0.17 0 0) *
##                       911) reimbursement2008>=4780 54   36 B1 (0.33 0.33 0.3 0.037 0)  
##                        1822) reimbursement2008>=13120 22   11 B2 (0.32 0.5 0.14 0.045 0)  
##                          3644) reimbursement2008< 14605 7    1 B2 (0.14 0.86 0 0 0) *
##                          3645) reimbursement2008>=14605 15    9 B1 (0.4 0.33 0.2 0.067 0) *
##                        1823) reimbursement2008< 13120 32   19 B3 (0.34 0.22 0.41 0.031 0)  
##                          3646) copd>=0.5 9    5 B1 (0.44 0.33 0.11 0.11 0) *
##                          3647) copd< 0.5 23   11 B3 (0.3 0.17 0.52 0 0) *
##                57) cancer>=0.5 119   75 B2 (0.3 0.37 0.22 0.11 0)  
##                 114) reimbursement2008< 6095 55   34 B1 (0.38 0.27 0.22 0.13 0)  
##                   228) heart.failure< 0.5 42   24 B1 (0.43 0.36 0.095 0.12 0)  
##                     456) reimbursement2008< 3950 10    3 B2 (0.2 0.7 0.1 0 0) *
##                     457) reimbursement2008>=3950 32   16 B1 (0.5 0.25 0.094 0.16 0)  
##                       914) age>=64.5 25   12 B1 (0.52 0.28 0 0.2 0)  
##                        1828) copd< 0.5 18    7 B1 (0.61 0.17 0 0.22 0) *
##                        1829) copd>=0.5 7    3 B2 (0.29 0.57 0 0.14 0) *
##                       915) age< 64.5 7    4 B1 (0.43 0.14 0.43 0 0) *
##                   229) heart.failure>=0.5 13    5 B3 (0.23 0 0.62 0.15 0) *
##                 115) reimbursement2008>=6095 64   35 B2 (0.23 0.45 0.22 0.094 0)  
##                   230) copd< 0.5 41   18 B2 (0.22 0.56 0.12 0.098 0) *
##                   231) copd>=0.5 23   14 B3 (0.26 0.26 0.39 0.087 0)  
##                     462) reimbursement2008>=9740 12    7 B1 (0.42 0.17 0.25 0.17 0) *
##                     463) reimbursement2008< 9740 11    5 B3 (0.091 0.36 0.55 0 0) *
##              29) depression>=0.5 320  190 B2 (0.3 0.41 0.23 0.066 0)  
##                58) copd< 0.5 213  129 B2 (0.35 0.39 0.2 0.056 0)  
##                 116) age< 55.5 20    9 B1 (0.55 0.15 0.3 0 0) *
##                 117) age>=55.5 193  112 B2 (0.33 0.42 0.19 0.062 0)  
##                   234) age< 82.5 136   70 B2 (0.29 0.49 0.17 0.051 0)  
##                     468) heart.failure< 0.5 72   38 B2 (0.39 0.47 0.097 0.042 0)  
##                       936) reimbursement2008>=7260 27   11 B1 (0.59 0.3 0.074 0.037 0)  
##                        1872) reimbursement2008>=14045 11    5 B2 (0.45 0.55 0 0 0) *
##                        1873) reimbursement2008< 14045 16    5 B1 (0.69 0.12 0.12 0.062 0) *
##                       937) reimbursement2008< 7260 45   19 B2 (0.27 0.58 0.11 0.044 0)  
##                        1874) reimbursement2008< 3740 7    3 B1 (0.57 0.29 0.14 0 0) *
##                        1875) reimbursement2008>=3740 38   14 B2 (0.21 0.63 0.11 0.053 0)  
##                          3750) reimbursement2008< 4175 13    2 B2 (0.15 0.85 0 0 0) *
##                          3751) reimbursement2008>=4175 25   12 B2 (0.24 0.52 0.16 0.08 0)  
##                            7502) reimbursement2008< 5090 10    6 B1 (0.4 0.3 0.2 0.1 0) *
##                            7503) reimbursement2008>=5090 15    5 B2 (0.13 0.67 0.13 0.067 0) *
##                     469) heart.failure>=0.5 64   32 B2 (0.19 0.5 0.25 0.062 0)  
##                       938) ihd< 0.5 12    2 B2 (0.083 0.83 0.083 0 0) *
##                       939) ihd>=0.5 52   30 B2 (0.21 0.42 0.29 0.077 0)  
##                        1878) osteoporosis>=0.5 13    4 B2 (0.15 0.69 0.077 0.077 0) *
##                        1879) osteoporosis< 0.5 39   25 B3 (0.23 0.33 0.36 0.077 0)  
##                          3758) reimbursement2008>=5860 25   13 B2 (0.2 0.48 0.24 0.08 0)  
##                            7516) reimbursement2008< 19195 18    8 B2 (0.22 0.56 0.17 0.056 0) *
##                            7517) reimbursement2008>=19195 7    4 B3 (0.14 0.29 0.43 0.14 0) *
##                          3759) reimbursement2008< 5860 14    6 B3 (0.29 0.071 0.57 0.071 0) *
##                   235) age>=82.5 57   33 B1 (0.42 0.26 0.23 0.088 0)  
##                     470) cancer< 0.5 46   24 B1 (0.48 0.2 0.22 0.11 0)  
##                       940) age>=91.5 13    3 B1 (0.77 0.15 0.077 0 0) *
##                       941) age< 91.5 33   21 B1 (0.36 0.21 0.27 0.15 0)  
##                        1882) kidney< 0.5 26   15 B1 (0.42 0.19 0.19 0.19 0) *
##                        1883) kidney>=0.5 7    3 B3 (0.14 0.29 0.57 0 0) *
##                     471) cancer>=0.5 11    5 B2 (0.18 0.55 0.27 0 0) *
##                59) copd>=0.5 107   61 B2 (0.21 0.43 0.28 0.084 0)  
##                 118) reimbursement2008>=25420 13    7 B3 (0.31 0.23 0.46 0 0) *
##                 119) reimbursement2008< 25420 94   51 B2 (0.19 0.46 0.26 0.096 0)  
##                   238) reimbursement2008>=17845 8    1 B2 (0 0.88 0 0.12 0) *
##                   239) reimbursement2008< 17845 86   50 B2 (0.21 0.42 0.28 0.093 0)  
##                     478) reimbursement2008< 15470 79   44 B2 (0.19 0.44 0.29 0.076 0)  
##                       956) age< 75.5 41   25 B2 (0.27 0.39 0.24 0.098 0)  
##                        1912) osteoporosis< 0.5 30   19 B1 (0.37 0.37 0.17 0.1 0)  
##                          3824) age>=68.5 15    7 B1 (0.53 0.27 0.2 0 0) *
##                          3825) age< 68.5 15    8 B2 (0.2 0.47 0.13 0.2 0) *
##                        1913) osteoporosis>=0.5 11    6 B2 (0 0.45 0.45 0.091 0) *
##                       957) age>=75.5 38   19 B2 (0.11 0.5 0.34 0.053 0)  
##                        1914) reimbursement2008>=4300 31   13 B2 (0.097 0.58 0.26 0.065 0) *
##                        1915) reimbursement2008< 4300 7    2 B3 (0.14 0.14 0.71 0 0) *
##                     479) reimbursement2008>=15470 7    4 B1 (0.43 0.14 0.14 0.29 0) *
##            15) diabetes>=0.5 3594 2105 B2 (0.21 0.41 0.21 0.14 0.021)  
##              30) kidney< 0.5 1568  880 B2 (0.29 0.44 0.19 0.075 0.007)  
##                60) arthritis< 0.5 964  571 B2 (0.34 0.41 0.19 0.062 0.0052)  
##                 120) cancer< 0.5 791  473 B2 (0.37 0.4 0.16 0.061 0.0051)  
##                   240) age< 70.5 277  163 B1 (0.41 0.33 0.19 0.069 0.0036)  
##                     480) reimbursement2008< 8845 199  109 B1 (0.45 0.36 0.16 0.025 0)  
##                       960) copd< 0.5 155   78 B1 (0.5 0.3 0.18 0.019 0)  
##                        1920) reimbursement2008>=6290 32   17 B1 (0.47 0.47 0.062 0 0)  
##                          3840) age< 57.5 8    3 B1 (0.62 0.25 0.12 0 0) *
##                          3841) age>=57.5 24   11 B2 (0.42 0.54 0.042 0 0)  
##                            7682) ihd< 0.5 7    3 B1 (0.57 0.43 0 0 0) *
##                            7683) ihd>=0.5 17    7 B2 (0.35 0.59 0.059 0 0) *
##                        1921) reimbursement2008< 6290 123   61 B1 (0.5 0.26 0.21 0.024 0)  
##                          3842) reimbursement2008>=5150 19    4 B1 (0.79 0.053 0.16 0 0) *
##                          3843) reimbursement2008< 5150 104   57 B1 (0.45 0.3 0.22 0.029 0)  
##                            7686) alzheimers< 0.5 76   37 B1 (0.51 0.22 0.24 0.026 0)  
##                             15372) osteoporosis>=0.5 20    6 B1 (0.7 0.15 0.1 0.05 0) *
##                             15373) osteoporosis< 0.5 56   31 B1 (0.45 0.25 0.29 0.018 0)  
##                               30746) reimbursement2008< 3745 17    6 B1 (0.65 0.24 0.12 0 0) *
##                               30747) reimbursement2008>=3745 39   25 B1 (0.36 0.26 0.36 0.026 0)  
##                                 61494) reimbursement2008>=4475 16   10 B1 (0.38 0.38 0.19 0.062 0) *
##                                 61495) reimbursement2008< 4475 23   12 B3 (0.35 0.17 0.48 0 0)  
##                                  122990) age< 59 10    5 B1 (0.5 0.2 0.3 0 0) *
##                                  122991) age>=59 13    5 B3 (0.23 0.15 0.62 0 0) *
##                            7687) alzheimers>=0.5 28   14 B2 (0.29 0.5 0.18 0.036 0) *
##                       961) copd>=0.5 44   19 B2 (0.3 0.57 0.091 0.045 0) *
##                     481) reimbursement2008>=8845 78   54 B1 (0.31 0.24 0.26 0.18 0.013)  
##                       962) reimbursement2008>=11475 52   36 B1 (0.31 0.31 0.17 0.19 0.019)  
##                        1924) copd< 0.5 31   19 B1 (0.39 0.35 0.065 0.16 0.032)  
##                          3848) age>=67.5 7    1 B1 (0.86 0.14 0 0 0) *
##                          3849) age< 67.5 24   14 B2 (0.25 0.42 0.083 0.21 0.042)  
##                            7698) osteoporosis>=0.5 9    5 B1 (0.44 0.22 0 0.22 0.11) *
##                            7699) osteoporosis< 0.5 15    7 B2 (0.13 0.53 0.13 0.2 0) *
##                        1925) copd>=0.5 21   14 B3 (0.19 0.24 0.33 0.24 0)  
##                          3850) age>=56.5 13    7 B3 (0.15 0.23 0.46 0.15 0) *
##                          3851) age< 56.5 8    5 B4 (0.25 0.25 0.12 0.38 0) *
##                       963) reimbursement2008< 11475 26   15 B3 (0.31 0.12 0.42 0.15 0)  
##                        1926) depression< 0.5 15    9 B1 (0.4 0.2 0.33 0.067 0) *
##                        1927) depression>=0.5 11    5 B3 (0.18 0 0.55 0.27 0) *
##                   241) age>=70.5 514  287 B2 (0.35 0.44 0.15 0.056 0.0058)  
##                     482) reimbursement2008>=5045 327  200 B1 (0.39 0.38 0.15 0.067 0.0092)  
##                       964) depression< 0.5 170   92 B1 (0.46 0.34 0.14 0.059 0.0059)  
##                        1928) age< 88.5 144   73 B1 (0.49 0.34 0.1 0.063 0)  
##                          3856) age>=73.5 117   56 B1 (0.52 0.3 0.11 0.068 0)  
##                            7712) reimbursement2008< 5335 11    3 B1 (0.73 0 0.18 0.091 0) *
##                            7713) reimbursement2008>=5335 106   53 B1 (0.5 0.33 0.1 0.066 0)  
##                             15426) reimbursement2008>=6040 85   39 B1 (0.54 0.33 0.12 0.012 0)  
##                               30852) reimbursement2008< 29020 76   32 B1 (0.58 0.32 0.11 0 0)  
##                                 61704) reimbursement2008>=8850 48   16 B1 (0.67 0.23 0.1 0 0) *
##                                 61705) reimbursement2008< 8850 28   15 B2 (0.43 0.46 0.11 0 0)  
##                                  123410) reimbursement2008< 6985 13    4 B1 (0.69 0.15 0.15 0 0) *
##                                  123411) reimbursement2008>=6985 15    4 B2 (0.2 0.73 0.067 0 0) *
##                               30853) reimbursement2008>=29020 9    5 B2 (0.22 0.44 0.22 0.11 0) *
##                             15427) reimbursement2008< 6040 21   14 B1 (0.33 0.33 0.048 0.29 0)  
##                               30854) alzheimers< 0.5 13    7 B1 (0.46 0.31 0.077 0.15 0) *
##                               30855) alzheimers>=0.5 8    4 B4 (0.12 0.38 0 0.5 0) *
##                          3857) age< 73.5 27   13 B2 (0.37 0.52 0.074 0.037 0)  
##                            7714) heart.failure>=0.5 13    6 B1 (0.54 0.38 0.077 0 0) *
##                            7715) heart.failure< 0.5 14    5 B2 (0.21 0.64 0.071 0.071 0) *
##                        1929) age>=88.5 26   17 B2 (0.27 0.35 0.31 0.038 0.038)  
##                          3858) age>=92.5 7    2 B2 (0.14 0.71 0.14 0 0) *
##                          3859) age< 92.5 19   12 B3 (0.32 0.21 0.37 0.053 0.053) *
##                       965) depression>=0.5 157   90 B2 (0.31 0.43 0.17 0.076 0.013)  
##                        1930) age>=88.5 28   13 B1 (0.54 0.32 0.036 0.071 0.036)  
##                          3860) age< 94.5 17    5 B1 (0.71 0.12 0.059 0.12 0) *
##                          3861) age>=94.5 11    4 B2 (0.27 0.64 0 0 0.091) *
##                        1931) age< 88.5 129   71 B2 (0.26 0.45 0.2 0.078 0.0078)  
##                          3862) alzheimers< 0.5 61   26 B2 (0.23 0.57 0.16 0.033 0)  
##                            7724) reimbursement2008>=14285 14    7 B1 (0.5 0.29 0.21 0 0) *
##                            7725) reimbursement2008< 14285 47   16 B2 (0.15 0.66 0.15 0.043 0)  
##                             15450) age< 81.5 26    5 B2 (0.12 0.81 0.077 0 0) *
##                             15451) age>=81.5 21   11 B2 (0.19 0.48 0.24 0.095 0)  
##                               30902) copd< 0.5 10    3 B2 (0.2 0.7 0 0.1 0) *
##                               30903) copd>=0.5 11    6 B3 (0.18 0.27 0.45 0.091 0) *
##                          3863) alzheimers>=0.5 68   45 B2 (0.29 0.34 0.24 0.12 0.015)  
##                            7726) reimbursement2008>=7090 49   30 B2 (0.31 0.39 0.14 0.14 0.02)  
##                             15452) stroke< 0.5 38   23 B1 (0.39 0.34 0.13 0.13 0)  
##                               30904) heart.failure>=0.5 26   13 B1 (0.5 0.27 0.12 0.12 0)  
##                                 61808) osteoporosis< 0.5 18    7 B1 (0.61 0.22 0 0.17 0) *
##                                 61809) osteoporosis>=0.5 8    5 B2 (0.25 0.38 0.38 0 0) *
##                               30905) heart.failure< 0.5 12    6 B2 (0.17 0.5 0.17 0.17 0) *
##                             15453) stroke>=0.5 11    5 B2 (0 0.55 0.18 0.18 0.091) *
##                            7727) reimbursement2008< 7090 19   10 B3 (0.26 0.21 0.47 0.053 0) *
##                     483) reimbursement2008< 5045 187   85 B2 (0.27 0.55 0.14 0.037 0)  
##                       966) age< 77.5 74   26 B2 (0.23 0.65 0.095 0.027 0)  
##                        1932) reimbursement2008< 4725 64   26 B2 (0.27 0.59 0.11 0.031 0)  
##                          3864) reimbursement2008< 4345 50   15 B2 (0.22 0.7 0.04 0.04 0) *
##                          3865) reimbursement2008>=4345 14    8 B1 (0.43 0.21 0.36 0 0) *
##                        1933) reimbursement2008>=4725 10    0 B2 (0 1 0 0 0) *
##                       967) age>=77.5 113   59 B2 (0.3 0.48 0.18 0.044 0)  
##                        1934) age< 78.5 9    3 B1 (0.67 0.11 0.22 0 0) *
##                        1935) age>=78.5 104   51 B2 (0.27 0.51 0.17 0.048 0)  
##                          3870) depression>=0.5 37   23 B1 (0.38 0.38 0.16 0.081 0)  
##                            7740) reimbursement2008< 4035 17    8 B1 (0.53 0.29 0.12 0.059 0) *
##                            7741) reimbursement2008>=4035 20   11 B2 (0.25 0.45 0.2 0.1 0)  
##                             15482) age>=86.5 7    4 B3 (0.29 0.29 0.43 0 0) *
##                             15483) age< 86.5 13    6 B2 (0.23 0.54 0.077 0.15 0) *
##                          3871) depression< 0.5 67   28 B2 (0.21 0.58 0.18 0.03 0) *
##                 121) cancer>=0.5 173   98 B2 (0.18 0.43 0.31 0.069 0.0058)  
##                   242) age>=82.5 39   12 B2 (0.1 0.69 0.15 0.026 0.026) *
##                   243) age< 82.5 134   86 B2 (0.21 0.36 0.35 0.082 0)  
##                     486) age>=55 120   74 B2 (0.21 0.38 0.32 0.092 0)  
##                       972) age< 59.5 8    1 B2 (0.12 0.88 0 0 0) *
##                       973) age>=59.5 112   73 B2 (0.21 0.35 0.34 0.098 0)  
##                        1946) age< 71.5 49   33 B1 (0.33 0.27 0.33 0.082 0)  
##                          3892) copd>=0.5 16    8 B1 (0.5 0.25 0.12 0.12 0) *
##                          3893) copd< 0.5 33   19 B3 (0.24 0.27 0.42 0.061 0)  
##                            7786) reimbursement2008< 5825 11    5 B1 (0.55 0.18 0.27 0 0) *
##                            7787) reimbursement2008>=5825 22   11 B3 (0.091 0.32 0.5 0.091 0)  
##                             15574) heart.failure< 0.5 8    4 B2 (0.12 0.5 0.25 0.12 0) *
##                             15575) heart.failure>=0.5 14    5 B3 (0.071 0.21 0.64 0.071 0) *
##                        1947) age>=71.5 63   37 B2 (0.13 0.41 0.35 0.11 0)  
##                          3894) depression< 0.5 33   19 B3 (0.21 0.27 0.42 0.091 0)  
##                            7788) alzheimers< 0.5 26   17 B2 (0.23 0.35 0.35 0.077 0)  
##                             15576) age>=76.5 16   10 B3 (0.31 0.31 0.38 0 0) *
##                             15577) age< 76.5 10    6 B2 (0.1 0.4 0.3 0.2 0) *
##                            7789) alzheimers>=0.5 7    2 B3 (0.14 0 0.71 0.14 0) *
##                          3895) depression>=0.5 30   13 B2 (0.033 0.57 0.27 0.13 0)  
##                            7790) age< 75.5 13    2 B2 (0 0.85 0.077 0.077 0) *
##                            7791) age>=75.5 17   10 B3 (0.059 0.35 0.41 0.18 0) *
##                     487) age< 55 14    5 B3 (0.21 0.14 0.64 0 0) *
##                61) arthritis>=0.5 604  309 B2 (0.21 0.49 0.2 0.094 0.0099)  
##                 122) reimbursement2008< 3875 69   22 B2 (0.14 0.68 0.13 0.043 0) *
##                 123) reimbursement2008>=3875 535  287 B2 (0.21 0.46 0.21 0.1 0.011)  
##                   246) depression< 0.5 282  149 B2 (0.24 0.47 0.16 0.12 0.014)  
##                     492) alzheimers< 0.5 183  102 B2 (0.28 0.44 0.13 0.13 0.022)  
##                       984) reimbursement2008>=11200 56   35 B1 (0.38 0.36 0.11 0.11 0.054)  
##                        1968) copd< 0.5 38   19 B1 (0.5 0.32 0.053 0.11 0.026)  
##                          3936) age>=67.5 30   13 B1 (0.57 0.33 0.033 0.033 0.033) *
##                          3937) age< 67.5 8    5 B4 (0.25 0.25 0.12 0.38 0) *
##                        1969) copd>=0.5 18   10 B2 (0.11 0.44 0.22 0.11 0.11) *
##                       985) reimbursement2008< 11200 127   66 B2 (0.24 0.48 0.13 0.13 0.0079)  
##                        1970) reimbursement2008< 6240 85   47 B2 (0.32 0.45 0.13 0.094 0.012)  
##                          3940) age< 80.5 59   29 B2 (0.32 0.51 0.1 0.051 0.017)  
##                            7880) reimbursement2008< 4180 7    2 B1 (0.71 0.14 0.14 0 0) *
##                            7881) reimbursement2008>=4180 52   23 B2 (0.27 0.56 0.096 0.058 0.019)  
##                             15762) reimbursement2008>=4955 32   18 B2 (0.38 0.44 0.094 0.062 0.031)  
##                               31524) ihd< 0.5 8    2 B1 (0.75 0.25 0 0 0) *
##                               31525) ihd>=0.5 24   12 B2 (0.25 0.5 0.12 0.083 0.042) *
##                             15763) reimbursement2008< 4955 20    5 B2 (0.1 0.75 0.1 0.05 0) *
##                          3941) age>=80.5 26   18 B1 (0.31 0.31 0.19 0.19 0)  
##                            7882) osteoporosis< 0.5 18   10 B1 (0.44 0.28 0.17 0.11 0) *
##                            7883) osteoporosis>=0.5 8    5 B2 (0 0.38 0.25 0.38 0) *
##                        1971) reimbursement2008>=6240 42   19 B2 (0.095 0.55 0.14 0.21 0)  
##                          3942) age>=67.5 32   11 B2 (0.031 0.66 0.12 0.19 0) *
##                          3943) age< 67.5 10    7 B1 (0.3 0.2 0.2 0.3 0) *
##                     493) alzheimers>=0.5 99   47 B2 (0.16 0.53 0.21 0.1 0)  
##                       986) age>=79.5 37   22 B2 (0.27 0.41 0.14 0.19 0)  
##                        1972) heart.failure< 0.5 16   10 B1 (0.38 0.38 0.25 0 0) *
##                        1973) heart.failure>=0.5 21   12 B2 (0.19 0.43 0.048 0.33 0)  
##                          3946) age>=87 10    4 B2 (0.2 0.6 0 0.2 0) *
##                          3947) age< 87 11    6 B4 (0.18 0.27 0.091 0.45 0) *
##                       987) age< 79.5 62   25 B2 (0.097 0.6 0.26 0.048 0)  
##                        1974) reimbursement2008>=9010 17    4 B2 (0.059 0.76 0.12 0.059 0) *
##                        1975) reimbursement2008< 9010 45   21 B2 (0.11 0.53 0.31 0.044 0)  
##                          3950) reimbursement2008< 5595 23    7 B2 (0.087 0.7 0.13 0.087 0) *
##                          3951) reimbursement2008>=5595 22   11 B3 (0.14 0.36 0.5 0 0)  
##                            7902) reimbursement2008>=6650 15    8 B2 (0.2 0.47 0.33 0 0) *
##                            7903) reimbursement2008< 6650 7    1 B3 (0 0.14 0.86 0 0) *
##                   247) depression>=0.5 253  138 B2 (0.18 0.45 0.27 0.083 0.0079)  
##                     494) age>=40.5 241  131 B2 (0.19 0.46 0.26 0.087 0.0083)  
##                       988) age< 54.5 16    5 B2 (0.19 0.69 0.12 0 0) *
##                       989) age>=54.5 225  126 B2 (0.19 0.44 0.27 0.093 0.0089)  
##                        1978) reimbursement2008< 39120 216  118 B2 (0.19 0.45 0.26 0.083 0.0093)  
##                          3956) reimbursement2008>=15105 52   22 B2 (0.15 0.58 0.19 0.077 0)  
##                            7912) reimbursement2008< 23850 30    8 B2 (0.1 0.73 0.067 0.1 0) *
##                            7913) reimbursement2008>=23850 22   14 B2 (0.23 0.36 0.36 0.045 0)  
##                             15826) age>=72.5 12    5 B2 (0.17 0.58 0.25 0 0) *
##                             15827) age< 72.5 10    5 B3 (0.3 0.1 0.5 0.1 0) *
##                          3957) reimbursement2008< 15105 164   96 B2 (0.21 0.41 0.28 0.085 0.012)  
##                            7914) alzheimers< 0.5 90   47 B2 (0.2 0.48 0.22 0.089 0.011)  
##                             15828) osteoporosis< 0.5 53   28 B2 (0.26 0.47 0.13 0.11 0.019)  
##                               31656) copd>=0.5 10    5 B1 (0.5 0.2 0.1 0.1 0.1) *
##                               31657) copd< 0.5 43   20 B2 (0.21 0.53 0.14 0.12 0)  
##                                 63314) reimbursement2008>=4140 36   15 B2 (0.22 0.58 0.14 0.056 0)  
##                                  126628) reimbursement2008< 5440 13    2 B2 (0.077 0.85 0.077 0 0) *
##                                  126629) reimbursement2008>=5440 23   13 B2 (0.3 0.43 0.17 0.087 0)  
##                                    253258) reimbursement2008< 5980 7    3 B1 (0.57 0.29 0 0.14 0) *
##                                    253259) reimbursement2008>=5980 16    8 B2 (0.19 0.5 0.25 0.062 0) *
##                                 63315) reimbursement2008< 4140 7    4 B4 (0.14 0.29 0.14 0.43 0) *
##                             15829) osteoporosis>=0.5 37   19 B2 (0.11 0.49 0.35 0.054 0)  
##                               31658) age>=74.5 15    4 B2 (0 0.73 0.2 0.067 0) *
##                               31659) age< 74.5 22   12 B3 (0.18 0.32 0.45 0.045 0) *
##                            7915) alzheimers>=0.5 74   48 B3 (0.22 0.34 0.35 0.081 0.014)  
##                             15830) age< 79.5 46   27 B2 (0.15 0.41 0.39 0.043 0)  
##                               31660) reimbursement2008< 5620 10    3 B2 (0.1 0.7 0.2 0 0) *
##                               31661) reimbursement2008>=5620 36   20 B3 (0.17 0.33 0.44 0.056 0)  
##                                 63322) reimbursement2008>=8035 21   11 B2 (0.19 0.48 0.24 0.095 0)  
##                                  126644) age< 67.5 9    6 B1 (0.33 0.22 0.33 0.11 0) *
##                                  126645) age>=67.5 12    4 B2 (0.083 0.67 0.17 0.083 0) *
##                                 63323) reimbursement2008< 8035 15    4 B3 (0.13 0.13 0.73 0 0) *
##                             15831) age>=79.5 28   19 B1 (0.32 0.21 0.29 0.14 0.036)  
##                               31662) age< 84.5 9    3 B1 (0.67 0 0.11 0.11 0.11) *
##                               31663) age>=84.5 19   12 B3 (0.16 0.32 0.37 0.16 0) *
##                        1979) reimbursement2008>=39120 9    5 B3 (0.11 0.11 0.44 0.33 0) *
##                     495) age< 40.5 12    5 B3 (0 0.42 0.58 0 0) *
##              31) kidney>=0.5 2026 1225 B2 (0.15 0.4 0.23 0.19 0.033)  
##                62) reimbursement2008< 15095 1090  627 B2 (0.18 0.42 0.24 0.14 0.021)  
##                 124) arthritis< 0.5 638  402 B2 (0.22 0.37 0.24 0.15 0.025)  
##                   248) age>=44.5 612  383 B2 (0.23 0.37 0.23 0.15 0.026)  
##                     496) reimbursement2008>=6575 346  226 B2 (0.25 0.35 0.21 0.16 0.029)  
##                       992) age>=85.5 67   45 B1 (0.33 0.27 0.31 0.06 0.03)  
##                        1984) osteoporosis< 0.5 43   25 B1 (0.42 0.21 0.28 0.047 0.047)  
##                          3968) reimbursement2008< 8495 11    3 B1 (0.73 0 0.27 0 0) *
##                          3969) reimbursement2008>=8495 32   22 B1 (0.31 0.28 0.28 0.062 0.062)  
##                            7938) age< 96.5 24   15 B3 (0.29 0.33 0.38 0 0)  
##                             15876) reimbursement2008>=13055 13    7 B1 (0.46 0.23 0.31 0 0) *
##                             15877) reimbursement2008< 13055 11    6 B2 (0.091 0.45 0.45 0 0) *
##                            7939) age>=96.5 8    5 B1 (0.38 0.12 0 0.25 0.25) *
##                        1985) osteoporosis>=0.5 24   15 B2 (0.17 0.38 0.38 0.083 0)  
##                          3970) reimbursement2008< 9045 8    2 B2 (0 0.75 0.25 0 0) *
##                          3971) reimbursement2008>=9045 16    9 B3 (0.25 0.19 0.44 0.12 0) *
##                       993) age< 85.5 279  177 B2 (0.24 0.37 0.18 0.19 0.029)  
##                        1986) reimbursement2008< 6780 11    5 B1 (0.55 0.091 0.091 0.27 0) *
##                        1987) reimbursement2008>=6780 268  167 B2 (0.22 0.38 0.18 0.19 0.03)  
##                          3974) age< 77.5 177  108 B2 (0.26 0.39 0.14 0.18 0.028)  
##                            7948) reimbursement2008< 14365 169  100 B2 (0.25 0.41 0.12 0.18 0.03)  
##                             15896) age>=75.5 24   13 B1 (0.46 0.25 0.042 0.21 0.042)  
##                               31792) copd< 0.5 10    3 B1 (0.7 0 0.1 0.1 0.1) *
##                               31793) copd>=0.5 14    8 B2 (0.29 0.43 0 0.29 0) *
##                             15897) age< 75.5 145   82 B2 (0.22 0.43 0.14 0.18 0.028)  
##                               31794) stroke>=0.5 18    7 B2 (0.11 0.61 0.22 0.056 0) *
##                               31795) stroke< 0.5 127   75 B2 (0.24 0.41 0.13 0.2 0.031)  
##                                 63590) age>=68.5 65   34 B2 (0.25 0.48 0.15 0.11 0.015)  
##                                  127180) reimbursement2008< 10335 39   25 B1 (0.36 0.36 0.18 0.1 0)  
##                                    254360) reimbursement2008>=9355 8    3 B1 (0.62 0 0.12 0.25 0) *
##                                    254361) reimbursement2008< 9355 31   17 B2 (0.29 0.45 0.19 0.065 0)  
##                                      508722) heart.failure< 0.5 9    4 B1 (0.56 0.22 0.22 0 0) *
##                                      508723) heart.failure>=0.5 22   10 B2 (0.18 0.55 0.18 0.091 0)  
##                                       1017446) age< 71.5 12    3 B2 (0.17 0.75 0 0.083 0) *
##                                       1017447) age>=71.5 10    6 B3 (0.2 0.3 0.4 0.1 0) *
##                                  127181) reimbursement2008>=10335 26    9 B2 (0.077 0.65 0.12 0.12 0.038) *
##                                 63591) age< 68.5 62   41 B2 (0.23 0.34 0.097 0.29 0.048)  
##                                  127182) reimbursement2008>=10290 28   18 B4 (0.32 0.21 0.071 0.36 0.036)  
##                                    254364) reimbursement2008< 10940 7    3 B1 (0.57 0 0.29 0.14 0) *
##                                    254365) reimbursement2008>=10940 21   12 B4 (0.24 0.29 0 0.43 0.048)  
##                                      508730) alzheimers< 0.5 13    8 B2 (0.23 0.38 0 0.31 0.077) *
##                                      508731) alzheimers>=0.5 8    3 B4 (0.25 0.12 0 0.62 0) *
##                                  127183) reimbursement2008< 10290 34   19 B2 (0.15 0.44 0.12 0.24 0.059)  
##                                    254366) age< 65.5 25   12 B2 (0.16 0.52 0.12 0.12 0.08) *
##                                    254367) age>=65.5 9    4 B4 (0.11 0.22 0.11 0.56 0) *
##                            7949) reimbursement2008>=14365 8    4 B3 (0.38 0 0.5 0.12 0) *
##                          3975) age>=77.5 91   59 B2 (0.15 0.35 0.26 0.2 0.033)  
##                            7950) alzheimers< 0.5 34   23 B3 (0.26 0.24 0.32 0.12 0.059)  
##                             15900) copd>=0.5 10    5 B2 (0.2 0.5 0.2 0 0.1) *
##                             15901) copd< 0.5 24   15 B3 (0.29 0.12 0.38 0.17 0.042)  
##                               31802) cancer< 0.5 17   10 B1 (0.41 0.12 0.29 0.12 0.059) *
##                               31803) cancer>=0.5 7    3 B3 (0 0.14 0.57 0.29 0) *
##                            7951) alzheimers>=0.5 57   33 B2 (0.088 0.42 0.23 0.25 0.018)  
##                             15902) reimbursement2008>=9695 38   18 B2 (0.079 0.53 0.26 0.13 0)  
##                               31804) reimbursement2008< 13070 23   10 B2 (0.087 0.57 0.35 0 0)  
##                                 63608) reimbursement2008< 11420 13    4 B2 (0.077 0.69 0.23 0 0) *
##                                 63609) reimbursement2008>=11420 10    5 B3 (0.1 0.4 0.5 0 0) *
##                               31805) reimbursement2008>=13070 15    8 B2 (0.067 0.47 0.13 0.33 0) *
##                             15903) reimbursement2008< 9695 19   10 B4 (0.11 0.21 0.16 0.47 0.053) *
##                     497) reimbursement2008< 6575 266  157 B2 (0.19 0.41 0.26 0.12 0.023)  
##                       994) age>=92.5 19    5 B2 (0.16 0.74 0.053 0.053 0) *
##                       995) age< 92.5 247  152 B2 (0.19 0.38 0.27 0.13 0.024)  
##                        1990) age< 88.5 235  142 B2 (0.19 0.4 0.25 0.14 0.026)  
##                          3980) reimbursement2008< 6170 210  127 B2 (0.21 0.4 0.22 0.15 0.024)  
##                            7960) age>=81.5 48   23 B2 (0.19 0.52 0.15 0.12 0.021)  
##                             15920) depression< 0.5 25   15 B2 (0.32 0.4 0.12 0.12 0.04)  
##                               31840) alzheimers>=0.5 12    5 B1 (0.58 0.17 0.083 0.17 0) *
##                               31841) alzheimers< 0.5 13    5 B2 (0.077 0.62 0.15 0.077 0.077) *
##                             15921) depression>=0.5 23    8 B2 (0.043 0.65 0.17 0.13 0) *
##                            7961) age< 81.5 162  104 B2 (0.22 0.36 0.25 0.15 0.025)  
##                             15922) reimbursement2008< 4895 94   54 B2 (0.23 0.43 0.18 0.14 0.021)  
##                               31844) reimbursement2008< 4080 47   32 B1 (0.32 0.3 0.21 0.13 0.043)  
##                                 63688) age< 60.5 7    2 B2 (0.14 0.71 0.14 0 0) *
##                                 63689) age>=60.5 40   26 B1 (0.35 0.23 0.23 0.15 0.05)  
##                                  127378) age< 71.5 14    6 B1 (0.57 0.21 0.071 0.14 0) *
##                                  127379) age>=71.5 26   18 B3 (0.23 0.23 0.31 0.15 0.077)  
##                                    254758) reimbursement2008< 3885 19   13 B1 (0.32 0.21 0.21 0.16 0.11) *
##                                    254759) reimbursement2008>=3885 7    3 B3 (0 0.29 0.57 0.14 0) *
##                               31845) reimbursement2008>=4080 47   21 B2 (0.15 0.55 0.15 0.15 0) *
##                             15923) reimbursement2008>=4895 68   45 B3 (0.19 0.26 0.34 0.18 0.029)  
##                               31846) alzheimers< 0.5 39   27 B2 (0.28 0.31 0.23 0.15 0.026)  
##                                 63692) age>=76.5 15    9 B3 (0.27 0.33 0.4 0 0) *
##                                 63693) age< 76.5 24   17 B1 (0.29 0.29 0.12 0.25 0.042)  
##                                  127386) depression>=0.5 14    8 B2 (0.36 0.43 0.071 0.071 0.071) *
##                                  127387) depression< 0.5 10    5 B4 (0.2 0.1 0.2 0.5 0) *
##                               31847) alzheimers>=0.5 29   15 B3 (0.069 0.21 0.48 0.21 0.034) *
##                          3981) reimbursement2008>=6170 25   13 B3 (0.04 0.4 0.48 0.04 0.04)  
##                            7962) reimbursement2008>=6260 17    8 B2 (0 0.53 0.41 0 0.059) *
##                            7963) reimbursement2008< 6260 8    3 B3 (0.12 0.12 0.62 0.12 0) *
##                        1991) age>=88.5 12    4 B3 (0.17 0.17 0.67 0 0) *
##                   249) age< 44.5 26   11 B3 (0.038 0.27 0.58 0.12 0)  
##                     498) age< 34 7    3 B2 (0 0.57 0.43 0 0) *
##                     499) age>=34 19    7 B3 (0.053 0.16 0.63 0.16 0) *
##                 125) arthritis>=0.5 452  225 B2 (0.12 0.5 0.24 0.12 0.015)  
##                   250) reimbursement2008< 5300 143   58 B2 (0.14 0.59 0.15 0.1 0.007)  
##                     500) reimbursement2008>=5155 11    1 B2 (0 0.91 0 0.091 0) *
##                     501) reimbursement2008< 5155 132   57 B2 (0.15 0.57 0.17 0.11 0.0076)  
##                      1002) reimbursement2008< 4815 107   42 B2 (0.15 0.61 0.14 0.093 0.0093)  
##                        2004) reimbursement2008< 4595 88   38 B2 (0.18 0.57 0.16 0.08 0.011)  
##                          4008) reimbursement2008< 3725 19    5 B2 (0.11 0.74 0.053 0.11 0) *
##                          4009) reimbursement2008>=3725 69   33 B2 (0.2 0.52 0.19 0.072 0.014)  
##                            8018) osteoporosis>=0.5 29   15 B2 (0.34 0.48 0.1 0.069 0)  
##                             16036) reimbursement2008< 4270 22   10 B2 (0.41 0.55 0.045 0 0)  
##                               32072) reimbursement2008< 3905 7    3 B1 (0.57 0.29 0.14 0 0) *
##                               32073) reimbursement2008>=3905 15    5 B2 (0.33 0.67 0 0 0) *
##                             16037) reimbursement2008>=4270 7    5 B2 (0.14 0.29 0.29 0.29 0) *
##                            8019) osteoporosis< 0.5 40   18 B2 (0.1 0.55 0.25 0.075 0.025)  
##                             16038) reimbursement2008>=3995 31   11 B2 (0.097 0.65 0.16 0.065 0.032) *
##                             16039) reimbursement2008< 3995 9    4 B3 (0.11 0.22 0.56 0.11 0) *
##                        2005) reimbursement2008>=4595 19    4 B2 (0 0.79 0.053 0.16 0) *
##                      1003) reimbursement2008>=4815 25   15 B2 (0.16 0.4 0.28 0.16 0)  
##                        2006) reimbursement2008>=4975 16    8 B2 (0.19 0.5 0.19 0.12 0) *
##                        2007) reimbursement2008< 4975 9    5 B3 (0.11 0.22 0.44 0.22 0) *
##                   251) reimbursement2008>=5300 309  167 B2 (0.12 0.46 0.28 0.13 0.019)  
##                     502) ihd< 0.5 24   16 B3 (0.29 0.29 0.33 0.083 0)  
##                      1004) age>=70 16   10 B1 (0.38 0.31 0.19 0.12 0) *
##                      1005) age< 70 8    3 B3 (0.12 0.25 0.62 0 0) *
##                     503) ihd>=0.5 285  150 B2 (0.1 0.47 0.27 0.13 0.021)  
##                      1006) reimbursement2008>=5725 253  138 B2 (0.11 0.45 0.27 0.14 0.02)  
##                        2012) reimbursement2008< 6565 35   23 B3 (0.2 0.31 0.34 0.14 0)  
##                          4024) age< 72.5 13    7 B2 (0.23 0.46 0.15 0.15 0) *
##                          4025) age>=72.5 22   12 B3 (0.18 0.23 0.45 0.14 0) *
##                        2013) reimbursement2008>=6565 218  114 B2 (0.1 0.48 0.26 0.14 0.023)  
##                          4026) reimbursement2008>=7265 187  100 B2 (0.11 0.47 0.28 0.12 0.027)  
##                            8052) heart.failure< 0.5 35   21 B2 (0.2 0.4 0.2 0.17 0.029) *
##                            8053) heart.failure>=0.5 152   79 B2 (0.086 0.48 0.3 0.11 0.026)  
##                             16106) reimbursement2008< 13595 130   65 B2 (0.1 0.5 0.28 0.11 0.015)  
##                               32212) reimbursement2008>=10630 52   24 B2 (0.15 0.54 0.19 0.096 0.019)  
##                                 64424) reimbursement2008< 11260 14    2 B2 (0.071 0.86 0.071 0 0) *
##                                 64425) reimbursement2008>=11260 38   22 B2 (0.18 0.42 0.24 0.13 0.026)  
##                                  128850) alzheimers>=0.5 25   12 B2 (0.2 0.52 0.12 0.12 0.04) *
##                                  128851) alzheimers< 0.5 13    7 B3 (0.15 0.23 0.46 0.15 0) *
##                               32213) reimbursement2008< 10630 78   41 B2 (0.064 0.47 0.33 0.12 0.013)  
##                                 64426) depression< 0.5 37   17 B2 (0.081 0.54 0.27 0.11 0) *
##                                 64427) depression>=0.5 41   24 B2 (0.049 0.41 0.39 0.12 0.024)  
##                                  128854) reimbursement2008< 10175 34   18 B2 (0.029 0.47 0.35 0.12 0.029)  
##                                    257708) reimbursement2008>=9480 7    2 B2 (0 0.71 0.14 0.14 0) *
##                                    257709) reimbursement2008< 9480 27   16 B2 (0.037 0.41 0.41 0.11 0.037)  
##                                      515418) reimbursement2008< 9020 19   10 B2 (0.053 0.47 0.26 0.16 0.053) *
##                                      515419) reimbursement2008>=9020 8    2 B3 (0 0.25 0.75 0 0) *
##                                  128855) reimbursement2008>=10175 7    3 B3 (0.14 0.14 0.57 0.14 0) *
##                             16107) reimbursement2008>=13595 22   12 B3 (0 0.36 0.45 0.091 0.091)  
##                               32214) reimbursement2008>=14005 14    7 B2 (0 0.5 0.36 0 0.14) *
##                               32215) reimbursement2008< 14005 8    3 B3 (0 0.12 0.62 0.25 0) *
##                          4027) reimbursement2008< 7265 31   14 B2 (0.065 0.55 0.13 0.26 0) *
##                      1007) reimbursement2008< 5725 32   12 B2 (0 0.62 0.25 0.094 0.031)  
##                        2014) reimbursement2008>=5385 22    5 B2 (0 0.77 0.18 0 0.045) *
##                        2015) reimbursement2008< 5385 10    6 B3 (0 0.3 0.4 0.3 0) *
##                63) reimbursement2008>=15095 936  598 B2 (0.13 0.36 0.22 0.24 0.046)  
##                 126) ihd< 0.5 53   35 B2 (0.3 0.34 0.075 0.26 0.019)  
##                   252) reimbursement2008>=25800 20    9 B1 (0.55 0.25 0.05 0.15 0)  
##                     504) age< 79.5 11    2 B1 (0.82 0 0.091 0.091 0) *
##                     505) age>=79.5 9    4 B2 (0.22 0.56 0 0.22 0) *
##                   253) reimbursement2008< 25800 33   20 B2 (0.15 0.39 0.091 0.33 0.03)  
##                     506) age< 79.5 20    8 B2 (0.05 0.6 0.1 0.2 0.05)  
##                      1012) reimbursement2008< 22825 13    2 B2 (0.077 0.85 0 0 0.077) *
##                      1013) reimbursement2008>=22825 7    3 B4 (0 0.14 0.29 0.57 0) *
##                     507) age>=79.5 13    6 B4 (0.31 0.077 0.077 0.54 0) *
##                 127) ihd>=0.5 883  563 B2 (0.12 0.36 0.23 0.24 0.048)  
##                   254) reimbursement2008< 26375 396  261 B2 (0.17 0.34 0.25 0.2 0.043)  
##                     508) arthritis< 0.5 233  160 B2 (0.21 0.31 0.21 0.24 0.034)  
##                      1016) copd< 0.5 95   68 B1 (0.28 0.24 0.21 0.26 0)  
##                        2032) reimbursement2008>=18065 67   45 B1 (0.33 0.18 0.25 0.24 0)  
##                          4064) reimbursement2008>=18390 59   39 B1 (0.34 0.2 0.2 0.25 0)  
##                            8128) stroke>=0.5 10    5 B2 (0.4 0.5 0.1 0 0) *
##                            8129) stroke< 0.5 49   33 B1 (0.33 0.14 0.22 0.31 0)  
##                             16258) age< 86.5 41   26 B1 (0.37 0.17 0.22 0.24 0)  
##                               32516) depression>=0.5 23   11 B1 (0.52 0.087 0.13 0.26 0) *
##                               32517) depression< 0.5 18   12 B3 (0.17 0.28 0.33 0.22 0) *
##                             16259) age>=86.5 8    3 B4 (0.12 0 0.25 0.62 0) *
##                          4065) reimbursement2008< 18390 8    3 B3 (0.25 0 0.62 0.12 0) *
##                        2033) reimbursement2008< 18065 28   17 B2 (0.18 0.39 0.11 0.32 0)  
##                          4066) reimbursement2008< 16540 9    6 B1 (0.33 0.11 0.33 0.22 0) *
##                          4067) reimbursement2008>=16540 19    9 B2 (0.11 0.53 0 0.37 0) *
##                      1017) copd>=0.5 138   88 B2 (0.15 0.36 0.21 0.22 0.058)  
##                        2034) reimbursement2008>=22770 41   21 B2 (0.17 0.49 0.15 0.098 0.098)  
##                          4068) age< 83.5 32   13 B2 (0.12 0.59 0.12 0.094 0.062)  
##                            8136) reimbursement2008>=25510 7    4 B1 (0.43 0.14 0.14 0.29 0) *
##                            8137) reimbursement2008< 25510 25    7 B2 (0.04 0.72 0.12 0.04 0.08) *
##                          4069) age>=83.5 9    6 B1 (0.33 0.11 0.22 0.11 0.22) *
##                        2035) reimbursement2008< 22770 97   67 B2 (0.14 0.31 0.24 0.27 0.041)  
##                          4070) reimbursement2008< 21150 81   53 B2 (0.17 0.35 0.22 0.22 0.037)  
##                            8140) age< 73.5 35   18 B2 (0.14 0.49 0.17 0.14 0.057)  
##                             16280) age>=60 28   12 B2 (0.18 0.57 0.11 0.11 0.036) *
##                             16281) age< 60 7    4 B3 (0 0.14 0.43 0.29 0.14) *
##                            8141) age>=73.5 46   33 B4 (0.2 0.24 0.26 0.28 0.022)  
##                             16282) age>=75.5 39   28 B2 (0.23 0.28 0.23 0.23 0.026)  
##                               32564) age< 80 10    5 B3 (0.2 0.3 0.5 0 0) *
##                               32565) age>=80 29   20 B4 (0.24 0.28 0.14 0.31 0.034)  
##                                 65130) age>=83.5 22   14 B2 (0.27 0.36 0.14 0.23 0)  
##                                  130260) reimbursement2008>=17685 10    6 B1 (0.4 0.3 0.2 0.1 0) *
##                                  130261) reimbursement2008< 17685 12    7 B2 (0.17 0.42 0.083 0.33 0) *
##                                 65131) age< 83.5 7    3 B4 (0.14 0 0.14 0.57 0.14) *
##                             16283) age< 75.5 7    3 B4 (0 0 0.43 0.57 0) *
##                          4071) reimbursement2008>=21150 16    8 B4 (0 0.12 0.31 0.5 0.062) *
##                     509) arthritis>=0.5 163  101 B2 (0.11 0.38 0.31 0.15 0.055)  
##                      1018) heart.failure>=0.5 140   83 B2 (0.12 0.41 0.27 0.14 0.057)  
##                        2036) age>=65 125   71 B2 (0.14 0.43 0.26 0.13 0.048)  
##                          4072) reimbursement2008>=22510 36   19 B2 (0.11 0.47 0.36 0 0.056)  
##                            8144) reimbursement2008>=22930 29   13 B2 (0.1 0.55 0.31 0 0.034)  
##                             16288) age< 86 22    8 B2 (0.091 0.64 0.27 0 0) *
##                             16289) age>=86 7    4 B3 (0.14 0.29 0.43 0 0.14) *
##                            8145) reimbursement2008< 22930 7    3 B3 (0.14 0.14 0.57 0 0.14) *
##                          4073) reimbursement2008< 22510 89   52 B2 (0.15 0.42 0.21 0.18 0.045)  
##                            8146) reimbursement2008>=17640 55   33 B2 (0.24 0.4 0.16 0.16 0.036)  
##                             16292) reimbursement2008< 18970 20   11 B1 (0.45 0.2 0.2 0.15 0)  
##                               32584) depression>=0.5 10    6 B2 (0.3 0.4 0.3 0 0) *
##                               32585) depression< 0.5 10    4 B1 (0.6 0 0.1 0.3 0) *
##                             16293) reimbursement2008>=18970 35   17 B2 (0.11 0.51 0.14 0.17 0.057) *
##                            8147) reimbursement2008< 17640 34   19 B2 (0 0.44 0.29 0.21 0.059)  
##                             16294) age< 77 9    2 B2 (0 0.78 0.22 0 0) *
##                             16295) age>=77 25   17 B2 (0 0.32 0.32 0.28 0.08)  
##                               32590) age< 82.5 10    5 B3 (0 0.3 0.5 0.1 0.1) *
##                               32591) age>=82.5 15    9 B4 (0 0.33 0.2 0.4 0.067) *
##                        2037) age< 65 15    9 B3 (0 0.2 0.4 0.27 0.13) *
##                      1019) heart.failure< 0.5 23   11 B3 (0.043 0.22 0.52 0.17 0.043)  
##                        2038) copd< 0.5 13    8 B2 (0.077 0.38 0.23 0.23 0.077) *
##                        2039) copd>=0.5 10    1 B3 (0 0 0.9 0.1 0) *
##                   255) reimbursement2008>=26375 487  302 B2 (0.076 0.38 0.21 0.28 0.051)  
##                     510) age>=88.5 65   28 B2 (0.11 0.57 0.11 0.15 0.062) *
##                     511) age< 88.5 422  274 B2 (0.071 0.35 0.23 0.3 0.05)  
##                      1022) reimbursement2008< 32040 91   47 B2 (0.066 0.48 0.19 0.23 0.033)  
##                        2044) age>=72 47   22 B2 (0.064 0.53 0.21 0.13 0.064)  
##                          4088) osteoporosis< 0.5 30   10 B2 (0.067 0.67 0.067 0.13 0.067) *
##                          4089) osteoporosis>=0.5 17    9 B3 (0.059 0.29 0.47 0.12 0.059) *
##                        2045) age< 72 44   25 B2 (0.068 0.43 0.16 0.34 0)  
##                          4090) alzheimers< 0.5 11    4 B2 (0.091 0.64 0.18 0.091 0) *
##                          4091) alzheimers>=0.5 33   19 B4 (0.061 0.36 0.15 0.42 0)  
##                            8182) arthritis>=0.5 17    8 B2 (0 0.53 0.059 0.41 0) *
##                            8183) arthritis< 0.5 16    9 B4 (0.12 0.19 0.25 0.44 0) *
##                      1023) reimbursement2008>=32040 331  226 B4 (0.073 0.31 0.24 0.32 0.054)  
##                        2046) stroke>=0.5 97   58 B2 (0.062 0.4 0.18 0.29 0.072)  
##                          4092) copd< 0.5 26   17 B2 (0.23 0.35 0.19 0.19 0.038)  
##                            8184) depression< 0.5 13    7 B1 (0.46 0.15 0.15 0.15 0.077) *
##                            8185) depression>=0.5 13    6 B2 (0 0.54 0.23 0.23 0) *
##                          4093) copd>=0.5 71   41 B2 (0 0.42 0.17 0.32 0.085)  
##                            8186) reimbursement2008< 38625 13    7 B2 (0 0.46 0.38 0.077 0.077) *
##                            8187) reimbursement2008>=38625 58   34 B2 (0 0.41 0.12 0.38 0.086)  
##                             16374) age< 79.5 39   20 B2 (0 0.49 0.077 0.44 0)  
##                               32748) age>=63.5 26   12 B2 (0 0.54 0.12 0.35 0) *
##                               32749) age< 63.5 13    5 B4 (0 0.38 0 0.62 0) *
##                             16375) age>=79.5 19   14 B2 (0 0.26 0.21 0.26 0.26) *
##                        2047) stroke< 0.5 234  157 B4 (0.077 0.28 0.27 0.33 0.047)  
##                          4094) reimbursement2008>=37290 180  126 B2 (0.078 0.3 0.29 0.28 0.044)  
##                            8188) age< 82.5 150  101 B2 (0.093 0.33 0.28 0.25 0.047)  
##                             16376) reimbursement2008< 88685 139   91 B2 (0.1 0.35 0.26 0.26 0.036)  
##                               32752) reimbursement2008>=79435 7    2 B2 (0 0.71 0 0.29 0) *
##                               32753) reimbursement2008< 79435 132   89 B2 (0.11 0.33 0.27 0.26 0.038)  
##                                 65506) age>=68.5 72   48 B2 (0.15 0.33 0.19 0.28 0.042)  
##                                  131012) heart.failure>=0.5 65   41 B2 (0.14 0.37 0.2 0.25 0.046)  
##                                    262024) age>=72.5 46   27 B2 (0.11 0.41 0.24 0.17 0.065)  
##                                      524048) reimbursement2008>=52775 25   16 B2 (0.16 0.36 0.36 0.08 0.04)  
##                                       1048096) reimbursement2008>=59785 11    7 B1 (0.36 0.36 0.091 0.18 0) *
##                                       1048097) reimbursement2008< 59785 14    6 B3 (0 0.36 0.57 0 0.071) *
##                                      524049) reimbursement2008< 52775 21   11 B2 (0.048 0.48 0.095 0.29 0.095)  
##                                       1048098) copd< 0.5 7    1 B2 (0 0.86 0 0.14 0) *
##                                       1048099) copd>=0.5 14    9 B4 (0.071 0.29 0.14 0.36 0.14) *
##                                    262025) age< 72.5 19   11 B4 (0.21 0.26 0.11 0.42 0) *
##                                  131013) heart.failure< 0.5 7    3 B4 (0.29 0 0.14 0.57 0) *
##                                 65507) age< 68.5 60   38 B3 (0.05 0.32 0.37 0.23 0.033)  
##                                  131014) osteoporosis< 0.5 38   20 B3 (0.053 0.26 0.47 0.18 0.026)  
##                                    262028) reimbursement2008< 44435 16    6 B3 (0.12 0.12 0.62 0.12 0) *
##                                    262029) reimbursement2008>=44435 22   14 B2 (0 0.36 0.36 0.23 0.045)  
##                                      524058) depression>=0.5 12    6 B2 (0 0.5 0.17 0.25 0.083) *
##                                      524059) depression< 0.5 10    4 B3 (0 0.2 0.6 0.2 0) *
##                                  131015) osteoporosis>=0.5 22   13 B2 (0.045 0.41 0.18 0.32 0.045)  
##                                    262030) depression< 0.5 8    3 B2 (0.12 0.62 0.12 0.12 0) *
##                                    262031) depression>=0.5 14    8 B4 (0 0.29 0.21 0.43 0.071) *
##                             16377) reimbursement2008>=88685 11    5 B3 (0 0.091 0.55 0.18 0.18) *
##                            8189) age>=82.5 30   17 B4 (0 0.17 0.37 0.43 0.033)  
##                             16378) copd< 0.5 9    5 B3 (0 0.22 0.44 0.22 0.11) *
##                             16379) copd>=0.5 21   10 B4 (0 0.14 0.33 0.52 0)  
##                               32758) depression>=0.5 10    5 B3 (0 0.1 0.5 0.4 0) *
##                               32759) depression< 0.5 11    4 B4 (0 0.18 0.18 0.64 0) *
##                          4095) reimbursement2008< 37290 54   28 B4 (0.074 0.2 0.19 0.48 0.056)  
##                            8190) reimbursement2008< 35865 39   25 B4 (0.1 0.26 0.21 0.36 0.077)  
##                             16380) depression>=0.5 27   19 B2 (0.074 0.3 0.3 0.3 0.037)  
##                               32760) age>=70 19   12 B3 (0.11 0.32 0.37 0.21 0) *
##                               32761) age< 70 8    4 B4 (0 0.25 0.12 0.5 0.12) *
##                             16381) depression< 0.5 12    6 B4 (0.17 0.17 0 0.5 0.17) *
##                            8191) reimbursement2008>=35865 15    3 B4 (0 0.067 0.13 0.8 0) *
## [1] TRUE
replay.petrisim(pn=glb_analytics_pn, 
    replay.trans=(glb_analytics_avl_objs <- c(glb_analytics_avl_objs, 
        "model.selected")), flip_coord=TRUE)
## time trans    "bgn " "fit.data.training.all " "predict.data.new " "end " 
## 0.0000   multiple enabled transitions:  data.training.all data.new model.selected    firing:  data.training.all 
## 1.0000    1   2 1 0 0 
## 1.0000   multiple enabled transitions:  data.training.all data.new model.selected model.final data.training.all.prediction   firing:  data.new 
## 2.0000    2   1 1 1 0 
## 2.0000   multiple enabled transitions:  data.training.all data.new model.selected model.final data.training.all.prediction data.new.prediction   firing:  model.selected 
## 3.0000    3   0 2 1 0

glb_script_df <- rbind(glb_script_df, 
                   data.frame(chunk_label="fit.data.training.all", 
                              chunk_step_major=max(glb_script_df$chunk_step_major)+1, 
                              chunk_step_minor=0,
                              elapsed=(proc.time() - glb_script_tm)["elapsed"]))
print(tail(glb_script_df, 2))
##                    chunk_label chunk_step_major chunk_step_minor elapsed
## elapsed8            fit.models                5                0  19.860
## elapsed9 fit.data.training.all                6                0 230.456

Step 6: fit.data.training.all

if (glb_fin_mdl_id %in% names(glb_models_lst)) {
    warning("Final model same as user selected model")
    glb_fin_mdl <- glb_sel_mdl
} else {    
    print(mdl_feats_df <- myextract_mdl_feats( sel_mdl=glb_sel_mdl, 
                                               entity_df=glb_entity_df))
    
    # Sync with parameters in mydsutils.R
    ret_lst <- myfit_mdl_fn(model_id="Final",
                            indep_vars_vctr=mdl_feats_df$id,
                            rsp_var=glb_rsp_var, rsp_var_out=glb_rsp_var_out, 
                            fit_df=glb_entity_df,
                            model_method=glb_sel_mdl$method,
                            model_loss_mtrx=glb_model_metric_terms, # Automate this
                            model_summaryFunction=glb_sel_mdl$control$summaryFunction,
                            model_metric=glb_sel_mdl$metric,
                            model_metric_maximize=glb_sel_mdl$maximize)
    glb_fin_mdl <- glb_models_lst[["Final"]] 
}
## Warning: Final model same as user selected model
glb_script_df <- rbind(glb_script_df, 
                   data.frame(chunk_label="fit.data.training.all", 
    chunk_step_major=glb_script_df[nrow(glb_script_df), "chunk_step_major"], 
    chunk_step_minor=glb_script_df[nrow(glb_script_df), "chunk_step_minor"]+1,
                              elapsed=(proc.time() - glb_script_tm)["elapsed"]))
print(tail(glb_script_df, 2))
##                     chunk_label chunk_step_major chunk_step_minor elapsed
## elapsed9  fit.data.training.all                6                0 230.456
## elapsed10 fit.data.training.all                6                1 272.435
if (glb_is_regression) {
    glb_entity_df[, glb_rsp_var_out] <- predict(glb_fin_mdl, newdata=glb_entity_df)
    print(myplot_scatter(glb_entity_df, glb_rsp_var, glb_rsp_var_out, 
                         smooth=TRUE))
    glb_entity_df[, paste0(glb_rsp_var_out, ".err")] <- 
        abs(glb_entity_df[, glb_rsp_var_out] - glb_entity_df[, glb_rsp_var])
    print(head(orderBy(reformulate(c("-", paste0(glb_rsp_var_out, ".err"))), 
                       glb_entity_df)))                             
}    

if (glb_is_classification & glb_is_binomial) {
    stop("not implemented")
            if (any(class(glb_fin_mdl) %in% c("train"))) {
        glb_entity_df[, paste0(glb_rsp_var_out, ".proba")] <- 
            predict(glb_fin_mdl, newdata=glb_entity_df, type="prob")[, 2]
    } else  if (any(class(glb_fin_mdl) %in% c("rpart", "randomForest"))) {
        glb_entity_df[, paste0(glb_rsp_var_out, ".proba")] <- 
            predict(glb_fin_mdl, newdata=glb_entity_df, type="prob")[, 2]
    } else  if (class(glb_fin_mdl) == "glm") {
        stop("not implemented yet")
        glb_entity_df[, paste0(glb_rsp_var_out, ".proba")] <- 
            predict(glb_fin_mdl, newdata=glb_entity_df, type="response")
    } else  stop("not implemented yet")   

    require(ROCR)
    ROCRpred <- prediction(glb_entity_df[, paste0(glb_rsp_var_out, ".proba")],
                           glb_entity_df[, glb_rsp_var])
    ROCRperf <- performance(ROCRpred, "tpr", "fpr")
    plot(ROCRperf, colorize=TRUE, print.cutoffs.at=seq(0, 1, 0.1), text.adj=c(-0.2,1.7))
    
    thresholds_df <- data.frame(threshold=seq(0.0, 1.0, 0.1))
    thresholds_df$f.score <- sapply(1:nrow(thresholds_df), function(row_ix) 
        mycompute_classifier_f.score(mdl=glb_fin_mdl, obs_df=glb_entity_df, 
                                     proba_threshold=thresholds_df[row_ix, "threshold"], 
                                      rsp_var=glb_rsp_var, 
                                      rsp_var_out=glb_rsp_var_out))
    print(thresholds_df)
    print(myplot_line(thresholds_df, "threshold", "f.score"))
    
    proba_threshold <- thresholds_df[which.max(thresholds_df$f.score), 
                                             "threshold"]
    # This should change to maximize f.score.OOB ???
    print(sprintf("Classifier Probability Threshold: %0.4f to maximize f.score.fit",
                  proba_threshold))
    if (is.null(glb_clf_proba_threshold)) 
        glb_clf_proba_threshold <- proba_threshold else {
        print(sprintf("Classifier Probability Threshold: %0.4f per user specs",
                      glb_clf_proba_threshold))
    }

    if ((class(glb_entity_df[, glb_rsp_var]) != "factor") | 
        (length(levels(glb_entity_df[, glb_rsp_var])) != 2))
        stop("expecting a factor with two levels:", glb_rsp_var)
    glb_entity_df[, glb_rsp_var_out] <- 
        factor(levels(glb_entity_df[, glb_rsp_var])[
            (glb_entity_df[, paste0(glb_rsp_var_out, ".proba")] >= 
                glb_clf_proba_threshold) * 1 + 1])
             
    print(mycreate_xtab(glb_entity_df, c(glb_rsp_var, glb_rsp_var_out)))
    print(sprintf("f.score=%0.4f", 
        mycompute_classifier_f.score(glb_fin_mdl, glb_entity_df, 
                                     glb_clf_proba_threshold, 
                                     glb_rsp_var, glb_rsp_var_out)))    
}

if (glb_is_classification & !glb_is_binomial) {
    glb_entity_df[, glb_rsp_var_out] <- predict(glb_fin_mdl, newdata=glb_entity_df, type="raw")
}    

print(glb_feats_df <- mymerge_feats_importance(feats_df=glb_feats_df, sel_mdl=glb_fin_mdl, 
                                               entity_df=glb_entity_df))
##                   id       cor.y exclude.as.feat  cor.y.abs cor.low
## 16 reimbursement2008  0.37372205               0 0.37372205       0
## 5         bucket2008  0.44817654               0 0.44817654       1
## 13               ihd  0.39279189               0 0.39279189       1
## 11          diabetes  0.39573574               0 0.39573574       1
## 12     heart.failure  0.36422152               0 0.36422152       1
## 2                age  0.04031166               0 0.04031166       1
## 14            kidney  0.37366230               0 0.37366230       1
## 9               copd  0.32033790               0 0.32033790       1
## 10        depression  0.28097857               0 0.28097857       1
## 4          arthritis  0.26626508               0 0.26626508       1
## 15      osteoporosis  0.20680648               0 0.20680648       1
## 3         alzheimers  0.27426278               0 0.27426278       1
## 8             cancer  0.19625387               0 0.19625387       1
## 18            stroke  0.18044011               0 0.18044011       1
## 1             .rnorm -0.01473661               0 0.01473661       1
## 6    bucket2008.fctr  0.44817654               1 0.44817654       0
## 7         bucket2009  1.00000000               1 1.00000000       0
## 17 reimbursement2009  0.85935358               1 0.85935358       0
##    importance
## 16 100.000000
## 5   57.274848
## 13  50.948433
## 11  50.780091
## 12  39.392020
## 2   21.038580
## 14   7.702760
## 9    5.418716
## 10   5.384403
## 4    4.529488
## 15   4.115735
## 3    3.332969
## 8    2.121192
## 18   0.000000
## 1          NA
## 6          NA
## 7          NA
## 17         NA
# Most of this code is used again in predict.data.new chunk
glb_analytics_diag_plots <- function(obs_df) {
    for (var in subset(glb_feats_df, !is.na(importance))$id) {
        plot_df <- melt(obs_df, id.vars=var, 
                        measure.vars=c(glb_rsp_var, glb_rsp_var_out))
#         if (var == "<feat_name>") print(myplot_scatter(plot_df, var, "value", 
#                                              facet_colcol_name="variable") + 
#                       geom_vline(xintercept=<divider_val>, linetype="dotted")) else     
            print(myplot_scatter(plot_df, var, "value", colorcol_name="variable",
                                 facet_colcol_name="variable", jitter=TRUE) + 
                      guides(color=FALSE))
    }
    
    if (glb_is_regression) {
        plot_vars_df <- subset(glb_feats_df, Pr.z < 0.1)
        print(myplot_prediction_regression(obs_df, 
                    ifelse(nrow(plot_vars_df) > 1, plot_vars_df$id[2], ".rownames"), 
                                           plot_vars_df$id[1],
                    glb_rsp_var, glb_rsp_var_out)
#               + facet_wrap(reformulate(plot_vars_df$id[2])) # if [1,2] is a factor                                                         
#               + geom_point(aes_string(color="<col_name>.fctr")) #  to color the plot
              )
    }    
    
    if (glb_is_classification) {
        if (nrow(plot_vars_df <- subset(glb_feats_df, !is.na(importance))) == 0)
            warning("No features in selected model are statistically important")
        else print(myplot_prediction_classification(df=obs_df, 
                feat_x=ifelse(nrow(plot_vars_df) > 1, plot_vars_df$id[2], 
                              ".rownames"),
                                               feat_y=plot_vars_df$id[1],
                     rsp_var=glb_rsp_var, 
                     rsp_var_out=glb_rsp_var_out, 
                     id_vars=glb_id_vars)
#               + geom_hline(yintercept=<divider_val>, linetype = "dotted")
                )
    }    
}
glb_analytics_diag_plots(obs_df=glb_entity_df)

##        age alzheimers arthritis cancer copd depression diabetes
## 15      86          0         0      0    0          0        0
## 122834  87          0         0      0    0          0        0
## 128526  38          0         0      0    0          0        0
## 134667  78          0         0      0    0          1        0
## 136745  45          0         1      0    0          0        1
## 139337  90          1         1      0    0          0        1
##        heart.failure ihd kidney osteoporosis stroke reimbursement2008
## 15                 0   0      0            0      0                 0
## 122834             1   0      1            0      1             69360
## 128526             0   0      0            1      0               200
## 134667             0   0      0            1      0              2480
## 136745             0   0      0            0      0               240
## 139337             1   0      0            0      0              1800
##        bucket2008 reimbursement2009 bucket2009      .rnorm bucket2009.fctr
## 15              1                 0          1  0.03766206              B1
## 122834          5               190          1  0.71149423              B1
## 128526          1               250          1 -0.67781422              B1
## 134667          1               320          1  0.08879450              B1
## 136745          1               350          1 -1.36179702              B1
## 139337          1               380          1 -0.48998431              B1
##        bucket2008.fctr bucket2009.fctr.predict.
## 15                  B1                       B1
## 122834              B5                       B1
## 128526              B1                       B2
## 134667              B1                       B2
## 136745              B1                       B3
## 139337              B1                       B2
##        bucket2009.fctr.predict..accurate  .label
## 15                                  TRUE     .15
## 122834                              TRUE .122834
## 128526                             FALSE .128526
## 134667                             FALSE .134667
## 136745                             FALSE .136745
## 139337                             FALSE .139337
##        age alzheimers arthritis cancer copd depression diabetes
## 15      86          0         0      0    0          0        0
## 139337  90          1         1      0    0          0        1
## 194151  85          1         0      0    1          1        0
## 206634  56          1         0      0    0          1        0
## 263957  79          1         1      0    0          1        1
## 312437  85          0         0      0    0          0        0
##        heart.failure ihd kidney osteoporosis stroke reimbursement2008
## 15                 0   0      0            0      0                 0
## 139337             1   0      0            0      0              1800
## 194151             1   1      1            0      0             60940
## 206634             0   0      0            0      0             72400
## 263957             0   1      1            1      0             62140
## 312437             0   0      0            0      0                 0
##        bucket2008 reimbursement2009 bucket2009      .rnorm bucket2009.fctr
## 15              1                 0          1  0.03766206              B1
## 139337          1               380          1 -0.48998431              B1
## 194151          5              1070          1  1.08821966              B1
## 206634          5              1230          1 -0.10191155              B1
## 263957          5              2070          1  1.00539868              B1
## 312437          1              3140          2 -0.68344269              B2
##        bucket2008.fctr bucket2009.fctr.predict.
## 15                  B1                       B1
## 139337              B1                       B2
## 194151              B5                       B3
## 206634              B5                       B2
## 263957              B5                       B4
## 312437              B1                       B1
##        bucket2009.fctr.predict..accurate  .label
## 15                                  TRUE     .15
## 139337                             FALSE .139337
## 194151                             FALSE .194151
## 206634                             FALSE .206634
## 263957                             FALSE .263957
## 312437                             FALSE .312437
##        age alzheimers arthritis cancer copd depression diabetes
## 310695  78          0         0      0    0          0        0
## 312437  85          0         0      0    0          0        0
## 312438  75          0         0      0    0          0        0
## 312790  75          0         0      0    0          0        0
## 313477  82          0         0      0    0          0        0
## 456653  82          1         1      0    1          1        1
##        heart.failure ihd kidney osteoporosis stroke reimbursement2008
## 310695             0   0      0            0      0                 0
## 312437             0   0      0            0      0                 0
## 312438             0   0      0            0      0                 0
## 312790             0   0      0            0      0                 0
## 313477             0   0      0            0      0                 0
## 456653             1   1      1            1      1            193590
##        bucket2008 reimbursement2009 bucket2009     .rnorm bucket2009.fctr
## 310695          1              3090          2 -1.3230033              B2
## 312437          1              3140          2 -0.6834427              B2
## 312438          1              3140          2 -0.8710372              B2
## 312790          1              3150          2 -0.2396126              B2
## 313477          1              3170          2  0.4760316              B2
## 456653          5             63750          5 -1.9277580              B5
##        bucket2008.fctr bucket2009.fctr.predict.
## 310695              B1                       B1
## 312437              B1                       B1
## 312438              B1                       B1
## 312790              B1                       B1
## 313477              B1                       B1
## 456653              B5                       B2
##        bucket2009.fctr.predict..accurate  .label
## 310695                             FALSE .310695
## 312437                             FALSE .312437
## 312438                             FALSE .312438
## 312790                             FALSE .312790
## 313477                             FALSE .313477
## 456653                             FALSE .456653

replay.petrisim(pn=glb_analytics_pn, 
    replay.trans=(glb_analytics_avl_objs <- c(glb_analytics_avl_objs, 
        "data.training.all.prediction","model.final")), flip_coord=TRUE)
## time trans    "bgn " "fit.data.training.all " "predict.data.new " "end " 
## 0.0000   multiple enabled transitions:  data.training.all data.new model.selected    firing:  data.training.all 
## 1.0000    1   2 1 0 0 
## 1.0000   multiple enabled transitions:  data.training.all data.new model.selected model.final data.training.all.prediction   firing:  data.new 
## 2.0000    2   1 1 1 0 
## 2.0000   multiple enabled transitions:  data.training.all data.new model.selected model.final data.training.all.prediction data.new.prediction   firing:  model.selected 
## 3.0000    3   0 2 1 0 
## 3.0000   multiple enabled transitions:  model.final data.training.all.prediction data.new.prediction     firing:  data.training.all.prediction 
## 4.0000    5   0 1 1 1 
## 4.0000   multiple enabled transitions:  model.final data.training.all.prediction data.new.prediction     firing:  model.final 
## 5.0000    4   0 0 2 1

glb_script_df <- rbind(glb_script_df, 
                   data.frame(chunk_label="predict.data.new", 
                              chunk_step_major=max(glb_script_df$chunk_step_major)+1, 
                              chunk_step_minor=0,
                              elapsed=(proc.time() - glb_script_tm)["elapsed"]))
print(tail(glb_script_df, 2))
##                     chunk_label chunk_step_major chunk_step_minor elapsed
## elapsed10 fit.data.training.all                6                1 272.435
## elapsed11      predict.data.new                7                0 322.880

Step 7: predict data.new

if (glb_is_regression)
    glb_newent_df[, glb_rsp_var_out] <- predict(glb_fin_mdl, 
                                        newdata=glb_newent_df, type="response")

if (glb_is_classification & glb_is_binomial) {
    # Compute selected model predictions
            if (any(class(glb_fin_mdl) %in% c("train"))) {
        glb_newent_df[, paste0(glb_rsp_var_out, ".proba")] <- 
            predict(glb_fin_mdl, newdata=glb_newent_df, type="prob")[, 2]
    } else  if (any(class(glb_fin_mdl) %in% c("rpart", "randomForest"))) {
        glb_newent_df[, paste0(glb_rsp_var_out, ".proba")] <- 
            predict(glb_fin_mdl, newdata=glb_newent_df, type="prob")[, 2]
    } else  if (class(glb_fin_mdl) == "glm") {
        stop("not implemented yet")
        glb_newent_df[, paste0(glb_rsp_var_out, ".proba")] <- 
            predict(glb_fin_mdl, newdata=glb_newent_df, type="response")
    } else  stop("not implemented yet")   

    if ((class(glb_newent_df[, glb_rsp_var]) != "factor") | 
        (length(levels(glb_newent_df[, glb_rsp_var])) != 2))
        stop("expecting a factor with two levels:", glb_rsp_var)
    glb_newent_df[, glb_rsp_var_out] <- 
        factor(levels(glb_newent_df[, glb_rsp_var])[
            (glb_newent_df[, paste0(glb_rsp_var_out, ".proba")] >= 
                glb_clf_proba_threshold) * 1 + 1])

    # Compute dummy model predictions
    glb_newent_df[, paste0(glb_rsp_var, ".predictdmy.proba")] <- 
        predict(glb_dmy_mdl, newdata=glb_newent_df, type="prob")[, 2]
    if ((class(glb_newent_df[, glb_rsp_var]) != "factor") | 
        (length(levels(glb_newent_df[, glb_rsp_var])) != 2))
        stop("expecting a factor with two levels:", glb_rsp_var)
    glb_newent_df[, paste0(glb_rsp_var, ".predictdmy")] <- 
        factor(levels(glb_newent_df[, glb_rsp_var])[
            (glb_newent_df[, paste0(glb_rsp_var, ".predictdmy.proba")] >= 
                glb_clf_proba_threshold) * 1 + 1])
}

if (glb_is_classification & !glb_is_binomial) {    
    # Compute final model predictions
    glb_rsp_var_out <- paste0(glb_rsp_var_out, "Final")
    glb_newent_df[, glb_rsp_var_out] <- 
        mypredict_mdl(glb_fin_mdl, glb_newent_df, glb_rsp_var, glb_rsp_var_out, 
                      "Final", "Final",
                                glb_model_metric_smmry, glb_model_metric, 
                                glb_model_metric_maximize, ret_type="raw")
}
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 11972  1166   232    56     0
##        B2  1955  1384   367    98     0
##        B3   889   657   183    60     0
##        B4   346   349   114    57     0
##        B5    39    48    18    10     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   6.798000e-01   2.897201e-01   6.732832e-01   6.862645e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   5.289133e-03  1.795989e-240
myprint_df(glb_newent_df[, c(glb_id_vars, glb_rsp_var, glb_rsp_var_out)])
##    bucket2009.fctr bucket2009.fctr.predict.Final
## 5               B1                            B1
## 25              B1                            B1
## 38              B1                            B1
## 60              B1                            B1
## 69              B1                            B1
## 83              B1                            B1
##        bucket2009.fctr bucket2009.fctr.predict.Final
## 20956               B1                            B1
## 116972              B1                            B1
## 294542              B1                            B1
## 344476              B2                            B2
## 378628              B2                            B1
## 387089              B2                            B2
##        bucket2009.fctr bucket2009.fctr.predict.Final
## 457902              B5                            B2
## 457910              B5                            B4
## 457924              B5                            B2
## 457964              B5                            B2
## 457995              B5                            B2
## 458003              B5                            B2
if (glb_is_regression) {
    print(sprintf("Total SSE: %0.4f", 
                  sum((glb_newent_df[, glb_rsp_var_out] - 
                        glb_newent_df[, glb_rsp_var]) ^ 2)))
    print(sprintf("RMSE: %0.4f", 
                  (sum((glb_newent_df[, glb_rsp_var_out] - 
                        glb_newent_df[, glb_rsp_var]) ^ 2) / nrow(glb_newent_df)) ^ 0.5))                        
    print(myplot_scatter(glb_newent_df, glb_rsp_var, glb_rsp_var_out, 
                         smooth=TRUE))
                         
    glb_newent_df[, paste0(glb_rsp_var_out, ".err")] <- 
        abs(glb_newent_df[, glb_rsp_var_out] - glb_newent_df[, glb_rsp_var])
    print(head(orderBy(reformulate(c("-", paste0(glb_rsp_var_out, ".err"))), 
                       glb_newent_df)))                                                      

#     glb_newent_df[, "<Output Pred variable>"] <- func(glb_newent_df[, glb_pred_var_name])                         
}                         

if (glb_is_classification & glb_is_binomial) {
    ROCRpred <- prediction(glb_newent_df[, paste0(glb_rsp_var_out, ".proba")],
                           glb_newent_df[, glb_rsp_var])
    print(sprintf("auc=%0.4f", auc <- as.numeric(performance(ROCRpred, "auc")@y.values)))   
    
    print(sprintf("probability threshold=%0.4f", glb_clf_proba_threshold))
    print(newent_conf_df <- mycreate_xtab(glb_newent_df, 
                                        c(glb_rsp_var, glb_rsp_var_out)))
    print(sprintf("f.score.sel=%0.4f", 
        mycompute_classifier_f.score(mdl=glb_fin_mdl, obs_df=glb_newent_df, 
                                     proba_threshold=glb_clf_proba_threshold, 
                                      rsp_var=glb_rsp_var, 
                                      rsp_var_out=glb_rsp_var_out)))
    print(sprintf("sensitivity=%0.4f", newent_conf_df[2, 3] / 
                      (newent_conf_df[2, 3] + newent_conf_df[2, 2])))
    print(sprintf("specificity=%0.4f", newent_conf_df[1, 2] / 
                      (newent_conf_df[1, 2] + newent_conf_df[1, 3])))
    print(sprintf("accuracy=%0.4f", (newent_conf_df[1, 2] + newent_conf_df[2, 3]) / 
                      (newent_conf_df[1, 2] + newent_conf_df[2, 3] + 
                       newent_conf_df[1, 3] + newent_conf_df[2, 2])))
    
    print(mycreate_xtab(glb_newent_df, c(glb_rsp_var, paste0(glb_rsp_var, ".predictdmy"))))
    print(sprintf("f.score.dmy=%0.4f", 
        mycompute_classifier_f.score(mdl=glb_dmy_mdl, obs_df=glb_newent_df, 
                                     proba_threshold=glb_clf_proba_threshold, 
                                      rsp_var=glb_rsp_var, 
                                      rsp_var_out=paste0(glb_rsp_var, ".predictdmy"))))
}    

if (glb_is_classification & !glb_is_binomial) {
    print(mypredict_mdl(glb_fin_mdl, glb_newent_df, glb_rsp_var, glb_rsp_var_out, 
                      "Final", "Final",
                                glb_model_metric_smmry, glb_model_metric, 
                                glb_model_metric_maximize, ret_type="stats"))    
}    
##          Prediction
## Reference    B1    B2    B3    B4    B5
##        B1 11972  1166   232    56     0
##        B2  1955  1384   367    98     0
##        B3   889   657   183    60     0
##        B4   346   349   114    57     0
##        B5    39    48    18    10     0
##       Accuracy          Kappa  AccuracyLower  AccuracyUpper   AccuracyNull 
##   6.798000e-01   2.897201e-01   6.732832e-01   6.862645e-01   6.713000e-01 
## AccuracyPValue  McnemarPValue 
##   5.289133e-03  1.795989e-240 
##   model_id max.Accuracy.Final max.AccuracyLower.Final
## 1    Final             0.6798               0.6732832
##   max.AccuracyUpper.Final max.Kappa.Final min.loss.error.Final
## 1               0.6862645       0.2897201              0.77965
glb_analytics_diag_plots(obs_df=glb_newent_df)

##        age alzheimers arthritis cancer copd depression diabetes
## 5       67          0         0      0    0          0        0
## 87815   69          0         0      0    0          0        0
## 89679   88          0         0      0    1          0        0
## 89842   73          1         0      0    0          1        1
## 89999   73          0         0      0    0          0        1
## 90007   79          1         0      0    0          0        0
## 98696   48          0         0      0    0          0        0
## 124148  79          1         0      0    1          1        1
## 213406  62          0         0      0    0          0        1
## 225905  69          0         0      1    0          0        1
## 256178  72          0         0      1    1          1        1
## 260504  99          1         0      0    1          0        1
## 271376  79          0         0      0    1          0        1
## 307825  63          0         0      0    0          0        0
## 308505  79          0         0      0    0          0        0
## 308509  47          0         0      0    0          0        0
## 310318  69          0         0      0    0          0        0
## 312436  46          0         0      0    0          0        0
## 314899  78          0         0      0    0          0        0
## 440173  71          1         0      1    1          1        1
##        heart.failure ihd kidney osteoporosis stroke reimbursement2008
## 5                  0   0      0            0      0                 0
## 87815              0   0      0            1      0               200
## 89679              0   0      0            1      0               910
## 89842              0   1      0            0      0              1390
## 89999              1   1      0            0      0              2680
## 90007              1   1      0            0      0              2840
## 98696              0   0      0            0      0              1150
## 124148             0   1      0            0      0             64230
## 213406             1   1      1            0      0             58010
## 225905             1   1      1            0      0             57820
## 256178             1   1      1            0      1            118010
## 260504             1   1      1            0      1             98710
## 271376             1   1      0            1      0             60890
## 307825             0   0      0            0      0                 0
## 308505             0   0      0            0      0                 0
## 308509             0   0      0            0      0                 0
## 310318             0   0      0            0      0                 0
## 312436             0   0      0            0      0                 0
## 314899             0   0      0            0      0                 0
## 440173             1   1      1            0      1            141660
##        bucket2008 reimbursement2009 bucket2009        .rnorm
## 5               1                 0          1  0.2563803995
## 87815           1                 0          1  0.4910679806
## 89679           1                 0          1  0.7226997051
## 89842           1                 0          1  1.1181769156
## 89999           1                 0          1  0.3429133458
## 90007           1                 0          1 -1.3700306672
## 98696           1                40          1 -0.0004705395
## 124148          5               200          1  0.3260885316
## 213406          5              1320          1  0.2801729340
## 225905          5              1490          1 -0.5685605363
## 256178          5              1940          1 -0.4634628358
## 260504          5              2010          1  1.3213277998
## 271376          5              2200          1 -0.7134561296
## 307825          1              3010          2  1.4136923229
## 308505          1              3030          2 -0.5108320838
## 308509          1              3030          2 -1.3886691729
## 310318          1              3080          2 -0.8107585209
## 312436          1              3140          2  1.4069063868
## 314899          1              3210          2 -1.1711047337
## 440173          5             21920          4  0.5521601622
##        bucket2009.fctr bucket2008.fctr bucket2009.fctr.predict.Final
## 5                   B1              B1                            B1
## 87815               B1              B1                            B2
## 89679               B1              B1                            B2
## 89842               B1              B1                            B2
## 89999               B1              B1                            B2
## 90007               B1              B1                            B3
## 98696               B1              B1                            B2
## 124148              B1              B5                            B2
## 213406              B1              B5                            B3
## 225905              B1              B5                            B4
## 256178              B1              B5                            B2
## 260504              B1              B5                            B2
## 271376              B1              B5                            B2
## 307825              B2              B1                            B1
## 308505              B2              B1                            B1
## 308509              B2              B1                            B1
## 310318              B2              B1                            B1
## 312436              B2              B1                            B1
## 314899              B2              B1                            B1
## 440173              B4              B5                            B2
##        bucket2009.fctr.predict.Final.accurate  .label
## 5                                        TRUE      .5
## 87815                                   FALSE  .87815
## 89679                                   FALSE  .89679
## 89842                                   FALSE  .89842
## 89999                                   FALSE  .89999
## 90007                                   FALSE  .90007
## 98696                                   FALSE  .98696
## 124148                                  FALSE .124148
## 213406                                  FALSE .213406
## 225905                                  FALSE .225905
## 256178                                  FALSE .256178
## 260504                                  FALSE .260504
## 271376                                  FALSE .271376
## 307825                                  FALSE .307825
## 308505                                  FALSE .308505
## 308509                                  FALSE .308509
## 310318                                  FALSE .310318
## 312436                                  FALSE .312436
## 314899                                  FALSE .314899
## 440173                                  FALSE .440173

tmp_replay_lst <- replay.petrisim(pn=glb_analytics_pn, 
    replay.trans=(glb_analytics_avl_objs <- c(glb_analytics_avl_objs, 
        "data.new.prediction")), flip_coord=TRUE)
## time trans    "bgn " "fit.data.training.all " "predict.data.new " "end " 
## 0.0000   multiple enabled transitions:  data.training.all data.new model.selected    firing:  data.training.all 
## 1.0000    1   2 1 0 0 
## 1.0000   multiple enabled transitions:  data.training.all data.new model.selected model.final data.training.all.prediction   firing:  data.new 
## 2.0000    2   1 1 1 0 
## 2.0000   multiple enabled transitions:  data.training.all data.new model.selected model.final data.training.all.prediction data.new.prediction   firing:  model.selected 
## 3.0000    3   0 2 1 0 
## 3.0000   multiple enabled transitions:  model.final data.training.all.prediction data.new.prediction     firing:  data.training.all.prediction 
## 4.0000    5   0 1 1 1 
## 4.0000   multiple enabled transitions:  model.final data.training.all.prediction data.new.prediction     firing:  model.final 
## 5.0000    4   0 0 2 1 
## 6.0000    6   0 0 1 2

#print(ggplot.petrinet(tmp_replay_lst[["pn"]]) + coord_flip())

Null Hypothesis (\(\sf{H_{0}}\)): mpg is not impacted by am_fctr.
The variance by am_fctr appears to be independent. #{r q1, cache=FALSE} # print(t.test(subset(cars_df, am_fctr == "automatic")$mpg, # subset(cars_df, am_fctr == "manual")$mpg, # var.equal=FALSE)$conf) # We reject the null hypothesis i.e. we have evidence to conclude that am_fctr impacts mpg (95% confidence). Manual transmission is better for miles per gallon versus automatic transmission.

```{r print_sessionInfo, echo=FALSE}

lcl_script_df <- glb_script_df rownames(lcl_script_df) <- seq(1, nrow(lcl_script_df)) lcl_script_df\(elapsed_diff <- sapply(seq(1, nrow(lcl_script_df)), function(step) ifelse(step <= 1, 0, lcl_script_df[step, "elapsed"] - lcl_script_df[step - 1, "elapsed"])) print(lcl_script_df[order(lcl_script_df\)elapsed_diff, decreasing=TRUE),]) print(sprintf(“Total Elapsed Time: %s secs”, format(lcl_script_df[nrow(lcl_script_df), “elapsed”], big.mark=‘,’))) tmp_script_df <- subset(lcl_script_df, chunk_step_minor == 0)[, c(“chunk_label”, “chunk_step_major”)] names(tmp_script_df)[1] <- “chunk_label_major” #print(tmp_script_df) plot_script_df <- merge(lcl_script_df, tmp_script_df, all.x=TRUE) plot_script_df\(chunk_step_major_desc <- max(plot_script_df\)chunk_step_major) - plot_script_df$chunk_step_major print(ggplot(plot_script_df, aes(x=reorder(chunk_label_major, chunk_step_major_desc), y=elapsed_diff, fill=factor(chunk_step_minor))) + geom_bar(stat=“identity”) + coord_flip())

remove nearZeroVar features (not much variance)

require(reshape)

var_features_df <- melt(summaryBy(. ~ factor(0), data=glb_entity_df[, features_lst],

FUN=var, keep.names=TRUE),

variable_name=c(“feature”))

names(var_features_df)[2] <- “var”

print(var_features_df[order(var_features_df$var), ])

summaryBy ignores factors whereas nearZeroVar inspects factors

k_fold <- 5

glb_entity_df[order(glb_entity_df\(classe, # glb_entity_df\)user_name, # glb_entity_df$my.rnorm),“my.cv_ix”] <-

rep(1:k_fold, length.out=nrow(glb_entity_df))

summaryBy(X ~ my.cv_ix, data=glb_entity_df, FUN=length)

tapply(glb_entity_df\(X, list(glb_entity_df\)classe, glb_entity_df\(user_name, # glb_entity_df\)my.cv_ix), length)

require(DAAG)

glb_entity_df\(classe.proper <- as.numeric(glb_entity_df\)classe == “A”)

rnorm.glm <- glm(classe.proper ~ rnorm, family=binomial, data=glb_entity_df)

cv.binary(rnorm.glm, nfolds=k_fold, print.details=TRUE)

result <- cv.lm(df=glb_entity_df, form.lm=formula(classe ~ rnorm),

m=k_fold, seed=12345, printit=TRUE)

plot(mdl_1\(finalModel, uniform=TRUE, main="base") #text(mdl_1\)finalModel, use.n=TRUE, all=TRUE, cex=0.8)

sessionInfo() #```